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Books

Book Series | Collections | Analytics | Semantic Analytics | Agents et al | R | Julia | C++ | .Net | Python | Scala | Java | Ethics | Statistics | Aggregation | Causal Inference | Decision Making | Mathematics | Visualization | Miscellaneous | Data Management | Internet of Things | BI
|Books| = 1484

Book Series

“Data and Analytics Series”
Addison-Wesley

Publisher
“R – Programming”
O’Reilly Media

Publisher
“Statistics”
Springer

Publisher
“The R Series”
Chapman & Hall/CRC

Publisher

Collections

“Amazon Best Sellers in AI & Machine Learning”


Publisher
“Amazon Best Sellers in Data Mining”


Publisher
“Data Science Books (datascience@berkeley)”


Publisher
“Dataviz Books”
(Civil Statistician )

Publisher
“Library of Peter Norvig”


Publisher
“Must Read Books in Analytics / Data Science”
Infographic

Publisher
“R-Project: Books related to R”


Publisher

Analytics

“A / B Testing”
The Most Powerful Way to Turn Clicks Into Customers

Publisher / Amazon
2013
“A Beginners Guide for Machine Learning”


Publisher / Amazon
2018
“A Computational Approach to Statistical Learning”


Publisher / Amazon
2019
“A Distributed Linear Programming Models in a Smart Grid”


Publisher / Amazon
2017
“A First Course in Machine Learning”
Second Edition

Publisher / Amazon
2016
“A Practical Guide to Analytics for Governments”
Using Big Data for Good

Publisher / Amazon
2017
“A Primer for Computational Biology”


Publisher / Amazon
2017
“A Primer on Process Mining”
Practical Skills with Python and Graphviz

Publisher / Amazon
2017
“A User’s Guide to Business Analytics”


Publisher / Amazon
2016
“A User’s Guide to Network Analysis in R”


Publisher / Amazon
2015
“Adaptation and Hybridization in Computational Intelligence”
(Adaptation, Learning, and Optimization)

Publisher / Amazon
2015
“Adaptive Regression for Modeling Nonlinear Relationships”


Publisher / Amazon
2016
“Adaptive Resonance Theory in Social Media Data Clustering”
Roles, Methodologies, and Applications

Publisher / Amazon
2019
“Adaptive Stochastic Optimization Techniques with Applications”


Publisher / Amazon
2015
“Advanced Analysis of Variance”


Publisher / Amazon
2017
“Advanced Analytics with Spark”


Publisher / Amazon
2015
“Advanced Business Analytics”
Essentials for Developing a Competitive Advantage

Publisher / Amazon
2016
“Advanced Customer Analytics”
Targeting, Valuing, Segmenting and Loyalty Techniques

Publisher / Amazon
2016
“Advanced Data Analysis in Neuroscience”
Integrating Statistical and Computational Models

Publisher / Amazon
2017
“Advanced Data Analytics in Health”


Publisher / Amazon
2018
“Advanced Data Analytics Using Python”
With Machine Learning, Deep Learning and NLP Examples

Publisher / Amazon
2018
“Advanced Deep Learning with Keras”
Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more

Publisher / Amazon
2018
“Advanced Optimization by Nature-Inspired Algorithms”


Publisher / Amazon
2018
“Advanced Planning and Scheduling in Manufacturing and Supply Chains”


Publisher / Amazon
2016
“Advanced R”
Data Programming and the Cloud

Publisher / Amazon
2016
“Advanced R Statistical Programming and Data Models”
Analysis, Machine Learning, and Visualization

Publisher / Amazon
2019
“Advanced Statistical Methods in Data Science”


Publisher / Amazon
2016
“Advanced Statistics for the Behavioral Sciences”
A Computational Approach with R

Publisher / Amazon
2018
“Advanced Time Series Data Analysis”
Forecasting Using EViews

Publisher / Amazon
2019
“Advances in Chaos Theory and Intelligent Control”


Publisher / Amazon
2016
“Advances in DEA Theory and Applications”
With Extensions to Forecasting Models

Publisher / Amazon
2017
“Advances in Financial Machine Learning”


Publisher / Amazon
2018
“Advances in Hybridization of Intelligent Methods”
Models, Systems and Applications

Publisher / Amazon
2018
“Advances in Metaheuristics Algorithms”
Methods and Applications

Publisher / Amazon
2018
“Advances in Neural Networks”
Computational Intelligence for ICT

Publisher / Amazon
2016
“Advances in Predictive Models and Methodologies for Numerically Efficient Linear and Nonlinear Analysis of Composites”


Publisher / Amazon
2019
“Algorithm Engineering”
Selected Results and Surveys

Publisher / Amazon
2016
“Algorithmische Graphentheorie”


Publisher / Amazon
2015
“Algorithms and Programs of Dynamic Mixture Estimation”
Unified Approach to Different Types of Components

Publisher / Amazon
2017
“Algorithms for Data Science”


Publisher / Amazon
2016
“Algorithms for Next-Generation Sequencing Data”
Techniques, Approaches, and Applications

Publisher / Amazon
2017
“Aligning Business Strategies and Analytics”
Bridging Between Theory and Practice

Publisher / Amazon
2019
“All Data Are Local”
Thinking Critically in a Data-Driven Society

Publisher / Amazon
2019
“An Economic Interpretation of Linear Programming”


Publisher / Amazon
2015
“An Introduction to Data”
Everything You Need to Know About AI, Big Data and Data Science

Publisher / Amazon
2019
“An Introduction to Fuzzy Linear Programming Problems”
Theory, Methods and Applications

Publisher / Amazon
2016
“An Introduction to Machine Learning”


Publisher / Amazon
2019
“An Introduction to Machine Learning”


Publisher / Amazon
2015
“An Introduction to Modeling Neuronal Dynamics”


Publisher / Amazon
2017
“An Introduction to Statistical Learning”
with Applications in R

Publisher / Amazon
2013
“An Introduction to Statistics with Python”
With Applications in the Life Sciences

Publisher / Amazon
2016
“Analyse des Anbieterwechsels mit Hidden-Markov-Modellen”
Empirische Untersuchung im Retail Banking

Publisher / Amazon
2015
“Analysis and Control of Coupled Neural Networks with Reaction-Diffusion Terms”


Publisher / Amazon
2018
“Analysis and Design of Markov Jump Systems with Complex Transition Probabilities”


Publisher / Amazon
2016
“Analysis and Presentation of Experimental Results”
With Examples, Problems and Programs

Publisher / Amazon
2017
“Analysis of Large and Complex Data”
Studies in Classification, Data Analysis, and Knowledge Organization

Publisher / Amazon
2016
“Analysis of Repeated Measures Data”


Publisher / Amazon
2017
“Analysis of Step-Stress Models”
Existing Results and Some Recent Developments

Publisher / Amazon
2017
“Analysis of Survival Data with Dependent Censoring”
Copula-Based Approaches

Publisher / Amazon
2018
“Analytical Methods for Dynamic Modelers”


Publisher / Amazon
2015
“Analytics for Insurance”
The Real Business of Big Data

Publisher / Amazon
2016
“Analytics for Smart Energy Management”
Tools and Applications for Sustainable Manufacturing

Publisher / Amazon
2016
“Analytics for the Internet of Things”
Application of Analytics to IoT devices

Publisher / Amazon
2016
“Analytics in a Big Data World”
Essential Guide to Data Science and its Applications

Publisher / Amazon
2014
“Analytics in Smart Tourism Design”
Concepts and Methods

Publisher / Amazon
2016
“Analyzing Time Interval Data”
Introducing an Information System for Time Interval Data Analysis

Publisher / Amazon
2016
“Angewandte Zeitreihenanalyse mit R”


Publisher / Amazon
2012
“Anomaly Detection Principles and Algorithms”


Publisher / Amazon
2017
“Application of Machine Learning- Classification of Students”


Publisher / Amazon
2018
“Applications of Artificial Intelligence Techniques in Industry 4.0”


Publisher / Amazon
2019
“Applications of Big Data Analytics”
Trends, Issues, and Challenges

Publisher / Amazon
2018
“Applied Analytics through Case Studies Using SAS and R”
Implementing Predictive Models and Machine Learning Techniques

Publisher / Amazon
2018
“Applied Compositional Data Analysis”
With Worked Examples in R

Publisher / Amazon
2018
“Applied Data Science”
Lessons Learned for the Data-Driven Business

Publisher / Amazon
2019
“Applied Fourier Analysis”
From Signal Processing to Medical Imaging

Publisher / Amazon
2017
“Applied Machine Learning”


Publisher / Amazon
2019
“Applied Multivariate Statistical Analysis”


Publisher / Amazon
2015
“Applied Predictive Analytics”
Principles and Techniques for the Professional Data Analyst

Publisher / Amazon
2014
“Applied Predictive Modeling”
Fundamental Concepts and Algorithms

Publisher / Amazon
2013
“Applied Probabilistic Calculus for Financial Engineering”
An Introduction Using R

Publisher / Amazon
2018
“Applied Probability”
From Random Sequences to Stochastic Processes

Publisher / Amazon
2018
“Applied Regression Analysis for Business”
Tools, Traps and Applications

Publisher / Amazon
2018
“Applied Surrogate Endpoint Evaluation Methods with SAS and R”


Publisher / Amazon
2016
“Applied Survival Analysis Using R”


Publisher / Amazon
2016
“Applied Time Series Analysis”
A Practical Guide to Modeling and Forecasting

Publisher / Amazon
2019
“Applied Time Series Analysis with R”


Publisher / Amazon
2016
“Applying Machine Learning for Automated Classification of Biomedical Data in Subject-Independent Settings”


Publisher / Amazon
2019
“Applying Predictive Analytics”
Finding Value in Data

Publisher / Amazon
2019
“Approximation and Optimization”
Algorithms, Complexity and Applications

Publisher / Amazon
2019
“Artificial Adaptive Systems using Auto Contractive Maps”
Theory, Applications and Extensions

Publisher / Amazon
2018
“Artificial Intelligence and Exponential Technologies”
Business Models Evolution and New Investment Opportunities

Publisher / Amazon
2017
“Artificial Intelligence and Games”


Publisher / Amazon
2018
“Artificial Intelligence and Natural Language Processing”


Publisher / Amazon
2018
“Artificial Intelligence Brings Positive or Negative Impaction to”
Influence Human Job Nature

Amazon
2019
“Artificial Intelligence Engines”
A Tutorial Introduction to the Mathematics of Deep Learning

Amazon
2019
“Artificial Intelligence for .NET”
Speech, Language, and Search: Building Smart Applications with Microsoft Cognitive Services APIs

Publisher / Amazon
2017
“Artificial Intelligence for Business”


Publisher / Amazon
2019
“Artificial Intelligence for Fashion Industry in the Big Data Era”


Publisher / Amazon
2018
“Artificial Intelligence for Marketing”
Practical Applications

Publisher / Amazon
2017
“Artificial Intelligence in Financial Markets”
Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics

Publisher / Amazon
2016
“Artificial Intelligence in IoT”


Publisher / Amazon
2019
“Artificial Intelligence Marketing and Predicting Consumer Choice”
An Overview of Tools and Techniques

Publisher / Amazon
“Artificial Intelligence Tools”
Decision Support Systems in Condition Monitoring and Diagnosis

Publisher / Amazon
2015
“Artificial Intelligence with Python”
A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers

Publisher / Amazon
2018
“Artificial Neural Network Applications for Software Reliability Prediction”


Publisher / Amazon
2017
“Artificial Neural Network Modelling”


Publisher / Amazon
2016
“Artificial Neural Networks”
A Practical Course

Publisher / Amazon
2016
“Artificial Neural Networks with Java”
Tools for Building Neural Network Applications

Publisher / Amazon
2019
“Asymmetric Kernel Smoothing”
Theory and Applications in Economics and Finance

Publisher / Amazon
2018
“Asymptotic Change-Point Analysis of the Dependencies in Time Series”


Publisher / Amazon
2016
“Asymptotic Nonparametric Statistical Analysis of Stationary Time Series”


Publisher / Amazon
2019
“Automated and Feature-Based Problem Characterization and Algorithm Selection Through Machine Learning”


Publisher
2018
“Automated Machine Learning”


Publisher / Amazon
2019
“Automated Trading with R”
Quantitative Research and Platform Development

Publisher / Amazon
2016
“Automatic Design of Decision-Tree Induction Algorithms”


Publisher / Amazon
2015
“Automatic Tuning of Compilers Using Machine Learning”


Publisher / Amazon
2018
“Autonomic Classification of IP Traffic in an NFV-based Network”
Using Supervised Machine Learning Algorithms

Publisher / Amazon
2018
“Basic Experimental Strategies and Data Analysis for Science and Engineering”


Publisher / Amazon
2016
“Bayesian Cost-Effectiveness Analysis with the R package BCEA”


Publisher / Amazon
2017
“Bayesian Data Analysis”


Publisher / Amazon
2013
“Bayesian Nonparametric Data Analysis”


Publisher / Amazon
2015
“Bayesian Reinforcement Learning”
A Survey

Publisher
2015
“Beautiful Data”
The Stories Behind Elegant Data Solutions

Publisher / Amazon
2009
“Beginning Artificial Intelligence with the Raspberry Pi”


Publisher / Amazon
2017
“Beginning Data Science in R”
Data Analysis, Visualization, and Modelling for the Data Scientist

Publisher / Amazon
2017
“Behavioral Operational Research”
Theory, Methodology and Practice

Publisher / Amazon
2016
“Behavioural Models”
From Modelling Finite Automata to Analysing Business Processes

Publisher / Amazon
2016
“BERRU Predictive Modeling”
Best Estimate Results with Reduced Uncertainties

Publisher / Amazon
2019
“Beyond Basic Statistics”
Tips, Tricks, and Techniques Every Data Analyst Should Know

Publisher / Amazon
2015
“Big and Complex Data Analysis”
Methodologies and Applications

Publisher / Amazon
2016
“Big Data”
A Business and Legal Guide

Publisher / Amazon
2014
“Big Data Analysis”
New Algorithms for a New Society

Publisher / Amazon
2016
“Big Data Analytics”
Methods and Applications

Publisher / Amazon
2016
“Big Data Analytics”
A Management Perspective

Publisher / Amazon
2016
“Big Data Analytics”
Handbook of Statistics

Publisher / Amazon
2015
“Big Data Analytics in Genomics”


Publisher / Amazon
2016
“Big Data Analytics with Spark”
A Practitioner’s Guide to Using Spark for Large Scale Data Analysis

Publisher / Amazon
2015
“Big Data and Analytics”
Strategic and Organizational Impacts

Publisher / Amazon
2015
“Big Data and Differential Privacy”
Analysis Strategies for Railway Track Engineering

Publisher / Amazon
2017
“Big Data and Learning Analytics in Higher Education”
Current Theory and Practice

Publisher / Amazon
2016
“Big Data and Social Science”
A Practical Guide to Methods and Tools

Publisher / Amazon
2016
“Big Data Concepts, Theories, and Applications”


Publisher / Amazon
2016
“Big Data Factories”
Collaborative Approaches

Publisher / Amazon
2017
“Big Data for Remote Sensing: Visualization, Analysis and Interpretation”
Digital Earth and Smart Earth

Publisher / Amazon
2019
“Big Data in Healthcare”
Extracting Knowledge from Point-of-Care Machines

Publisher / Amazon
2017
“Big Data Optimization”
Recent Developments and Challenges

Publisher / Amazon
2016
“Big Data Science and Analytics for Smart Sustainable Urbanism”
Unprecedented Paradigmatic Shifts and Practical Advancements

Publisher / Amazon
2019
“Big Data Technologies and Applications”


Publisher / Amazon
2016
“Big Data, Cloud Computing, and Data Science Engineering”


Publisher / Amazon
2020
“Big Data, Data Mining, and Machine Learning”
Value Creation for Business Leaders and Practitioners

Publisher / Amazon
2014
“Big Visual Data Analysis”
Scene Classification and Geometric Labeling

Publisher / Amazon
2016
“Big-Data Analytics and Cloud Computing”
Theory, Algorithms and Applications

Publisher / Amazon
2016
“Bilinear Regression Analysis”
An Introduction

Publisher / Amazon
2018
“Biostatistics and Computer-based Analysis of Health Data using R”


Publisher / Amazon
2016
“Boosted Statistical Relational Learners”
From Benchmarks to Data-Driven Medicine

Publisher / Amazon
2015
“Bootstrapping Machine Learning”
The first guide to Prediction APIs

Publisher / Amazon
2014
“Breakdown in Traffic Networks”
Fundamentals of Transportation Science

Publisher / Amazon
2017
“Bridging the Semantic Gap in Image and Video Analysis”


Publisher / Amazon
2018
“Bringing Bayesian Models to Life”


Publisher / Amazon
2019
“Building a Recommendation System with R”


Publisher / Amazon
2015
“Building Bots with Microsoft Bot Framework”
Creating intelligent conversational interfaces

Publisher / Amazon
2017
“Building Chatbots with Python”
Using Natural Language Processing and Machine Learning

Publisher / Amazon
2019
“Building Intelligent Systems”
A Guide to Machine Learning Engineering

Publisher
2018
“Building Machine Learning Powered Applications”
Going from Idea to Product

Publisher / Amazon
2019
“Building Recommendation Engines”
Understand your data and user preferences to make intelligent, accurate, and profitable decisions

Publisher / Amazon
2016
“Building Trading Bots Using Java”


Publisher / Amazon
2016
“Business Analytics Using R”
A Practical Approach

Publisher / Amazon
2017
“Business Statistics Using R”


Publisher / Amazon
2019
“Case-based Evidence – Grundlagen und Anwendung”
Prognose und Verbesserung der Akzeptanz von Produkten und Projekten

Publisher / Amazon
2016
“Case-Based Reasoning”
A Textbook

Publisher / Amazon
2013
“Categorical Data Analysis by Example”


Publisher / Amazon
2016
“Centrality and Diversity in Search”
Roles in A.I., Machine Learning, Social Networks, and Pattern Recognition

Publisher / Amazon
2019
“Challenges in Computational Statistics and Data Mining”


Publisher / Amazon
2016
“Characterizing Interdependencies of Multiple Time Series”
Theory and Applications

Publisher / Amazon
2017
“Classification from Antiquity to Modern Times”
Sources, Methods, and Theories from an Interdisciplinary Perspective

Publisher / Amazon
2017
“Classification in BioApps”
Automation of Decision Making

Publisher / Amazon
2018
“Classification, (Big) Data Analysis and Statistical Learning”


Publisher / Amazon
2018
“Clinical Data Analysis on a Pocket Calculator”
Understanding the Scientific Methods of Statistical Reasoning and Hypothesis Testing

Publisher / Amazon
2016
“Clinical Text Mining”
Secondary Use of Electronic Patient Records

Publisher / Amazon
2018
“Clustering Methods for Big Data Analytics”
Techniques, Toolboxes and Applications

Publisher / Amazon
2019
“Cognitive Computing”
Theory and Applications

Publisher / Amazon
2016
“Cognitive Computing for Big Data Systems Over IoT”
Frameworks, Tools and Applications

Publisher / Amazon
2018
“Cohort Intelligence”
A Socio-inspired Optimization Method

Publisher / Amazon
2016
“Combinatorial Optimization and Graph Algorithms”
Communications of NII Shonan Meetings

Publisher / Amazon
2017
“Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications”


Publisher / Amazon
2018
“Compact Extended Linear Programming Models”


Publisher / Amazon
2018
“Competition-Based Neural Networks with Robotic Applications”


Publisher / Amazon
2018
“Complex Event Processing”
Verarbeitung von Ereignismustern in Datenströmen

Publisher / Amazon
2017
“Complex Network Analysis in Python”
Recognize – Construct – Visualize – Analyze – Interpret

Publisher / Amazon
2017
“Complex Surveys”
Analysis of Categorical Data

Publisher / Amazon
2018
“Complexity of Seismic Time Series”
Measurement and Application

Publisher / Amazon
2018
“Comprehensive Analysis of Swarm Based Classifiers and Bayesian Based Models for Epilepsy Risk Level”


Publisher
2018
“Compression-Based Methods of Statistical Analysis and Prediction of Time Series”


Publisher / Amazon
2016
“Computational Actuarial Science with R”
A Hands-On Approach to Understanding and Using Actuarial Models

Publisher / Amazon
2014
“Computational and Statistical Methods for Application in Industry 4.0”


Publisher / Amazon
2019
“Computational Intelligence”
Eine methodische Einführung in Künstliche Neuronale Netze, Evolutionäre Algorithmen, Fuzzy-Systeme und Bayes-Netze

Publisher / Amazon
2015
“Computational Intelligence”
Probleme, Methoden Und Technische Anwendungen

Amazon
2016
“Computational Intelligence”
A Methodological Introduction

Publisher / Amazon
2016
“Computational Intelligence for Network Structure Analytics”


Publisher / Amazon
2017
“Computational Intelligence for Pattern Recognition”


Publisher / Amazon
2018
“Computational Intelligence Techniques in Health Care”


Publisher / Amazon
2016
“Computational Intelligent Data Analysis for Sustainable Development”


Publisher / Amazon
2016
“Computational Methods for Data Analysis”


Publisher / Amazon
2019
“Computational Metrics for Soccer Analysis”
Connecting the dots

Publisher / Amazon
2018
“Computational Personality Analysis”
Introduction, Practical Applications and Novel Directions

Publisher / Amazon
2016
“Conceptual Exploration”


Publisher / Amazon
2016
“Context-Aware Computing”


Publisher / Amazon
2018
“Convolution Copula Econometrics”


Publisher / Amazon
2016
“Correspondence Analysis in Practice”


Publisher / Amazon
2016
“Covariance Modelling”


Amazon
2019
“Creativity in Intelligent Technologies and Data Science”
Third Conference, CIT&DS 2019, Volgograd, Russia, September 16-19, 2019, Proceedings

Publisher / Amazon
2019
“Customer Churn Prediction Using Machine Learning Technique”


Publisher
2019
“Customer Relationship Analytics”
Praktische Anwendung des Data Mining im CRM

Publisher / Amazon
2015
“Data Analysis in the Cloud”
Models, Techniques and Applications

Publisher / Amazon
2015
“Data Analysis with R”


Publisher / Amazon
2018
“Data Analytics”
Models and Algorithms for Intelligent Data Analysis

Publisher / Amazon
2016
“Data Analytics for Intelligent Transportation Systems”


Publisher / Amazon
2017
“Data Analytics for Internal Auditors”


Publisher / Amazon
2017
“Data Analytics im Mittelstand”
Fundierter Einblick in das Modethema ‘Big Data’

Publisher / Amazon
2016
“Data Analytics in Digital Humanities”


Publisher / Amazon
2017
“Data Analytics in Professional Soccer”
Performance Analysis Based on Spatiotemporal Tracking Data

Publisher / Amazon
2018
“Data and Information Quality”
Dimensions, Principles and Techniques

Publisher / Amazon
2016
“Data Assimilation”
Mathematical Concepts and Instructive Examples

Publisher / Amazon
2015
“Data Assimilation”
A Mathematical Introduction

Publisher / Amazon
2015
“Data Classification”
Algorithms and Applications

Publisher / Amazon
2014
“Data Classification using Neural Analytics”


Publisher / Amazon
2017
“Data Clustering”
Algorithms and Applications

Publisher / Amazon
2013
“Data Clustering and Image Segmentation Through Genetic Algorithms”
Emerging Research and Opportunities

Publisher / Amazon
2019
“Data Envelopment Analysis”
From Normative to Descriptive Performance Evaluation

Publisher / Amazon
2017
“Data Envelopment Analysis”
A Handbook of Empirical Studies and Applications

Publisher / Amazon
2016
“Data Fitting and Uncertainty”
A practical introduction to weighted least squares and beyond

Publisher / Amazon
2016
“Data Mining”
The Textbook

Publisher / Amazon
2015
“Data Mining”


Amazon
2016
“Data Mining”
Practical Machine Learning Tools and Techniques

Publisher / Amazon
2016
“Data Mining”
Practical Machine Learning Tools and Techniques

Publisher / Amazon
2011
“Data Mining Algorithms”
Explained Using R

Publisher / Amazon
2015
“Data Mining and Analysis”
Fundamental Concepts and Algorithms

Publisher / Amazon
2014
“Data Mining and Constraint Programming”
Foundations of a Cross-Disciplinary Approach

Publisher / Amazon
2016
“Data Mining and Knowledge Discovery Handbook”


Publisher / Amazon
2010
“Data Mining for Managers”
How to Use Data (Big and Small) to Solve Business Challenges

Publisher / Amazon
2014
“Data Mining for Systems Biology”
Methods and Protocols

Publisher / Amazon
2018
“Data Mining Techniques for the Life Sciences”


Publisher / Amazon
2016
“Data Mining with Decision Trees”
Theory and Applications

Publisher / Amazon
2007
“Data Mining with SPSS Modeler”
Theory, Exercises and Solutions

Publisher / Amazon
2016
“Data Science”
Innovative Developments in Data Analysis and Clustering

Publisher / Amazon
2017
“Data Science”
Mindset, Methodologies, and Misconceptions

Publisher / Amazon
2017
“Data Science”
Create Teams That Ask the Right Questions and Deliver Real Value

Publisher / Amazon
2016
“Data Science”


Publisher / Amazon
2018
“Data Science and Big Data”
An Environment of Computational Intelligence

Publisher / Amazon
2017
“Data Science and Big Data Computing”
Frameworks and Methodologies

Publisher / Amazon
2016
“Data Science and Complex Networks”
Real Case Studies with Python

Publisher / Amazon
2016
“Data Science and Predictive Analytics”
Biomedical and Health Applications using R

Publisher / Amazon
2018
“Data Science for Business”
What you need to know about Data Mining and Data-Analytic Thinking

Publisher / Amazon
2013
“Data Science For Dummies”


Publisher / Amazon
2017
“Data Science for Healthcare”
Methodologies and Applications

Publisher / Amazon
2019
“Data Science for Supply Chain Forecast”


Amazon
2018
“Data Science for Transport”
A Self-Study Guide with Computer Exercises

Publisher
2018
“Data Science Foundations”
Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics

Publisher / Amazon
2017
“Data Science From Scratch”
First Principles with Python

Publisher / Amazon
2015
“Data Science Fundamentals for Python and MongoDB”


Publisher / Amazon
2018
“Data Science in Practice”


Publisher / Amazon
2019
“Data Scientist”
The Definitive Guide to Becoming a Data Scientist

Publisher / Amazon
2014
“Data Wrangling”
Munging in R with SQL and MongoDB for Financial Applications

Publisher / Amazon
2016
“Data Wrangling with R”


Publisher / Amazon
2016
“Data-Driven HR”
How to Use Analytics and Metrics to Drive Performance

Publisher / Amazon
2018
“Data-Driven Optimization and Knowledge Discovery for an Enterprise Information System”


Publisher / Amazon
2015
“Data-Driven Prediction for Industrial Processes and Their Applications”


Publisher / Amazon
2018
“Data-Intensive Science”


Publisher / Amazon
2016
“Data-Variant Kernel Analysis”


Publisher / Amazon
2015
“Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods”


Publisher / Amazon
2019
“Decision Tree and Ensemble Learning Based on Ant Colony Optimization”


Publisher / Amazon
2019
“Deep Learning”
Fundamentals, Theory and Applications

Publisher / Amazon
2019
“Deep Learning”
Convergence to Big Data Analytics

Publisher / Amazon
2019
“Deep Learning”
Practical Neural Networks with Java

Publisher / Amazon
2017
“Deep Learning”
A Practitioner’s Approach

Publisher / Amazon
2016
“Deep Learning and Convolutional Neural Networks for Medical Image Computing”
Precision Medicine, High Performance and Large-Scale Datasets

Publisher / Amazon
2017
“Deep Learning for Biometrics”


Publisher / Amazon
2017
“Deep Learning for Medical Image Analysis”


Publisher / Amazon
2017
“Deep Learning for Natural Language Processing”
Solve your natural language processing problems with smart deep neural networks

Publisher / Amazon
2019
“Deep Learning for Search”


Publisher / Amazon
2019
“Deep Learning for the Life Sciences”
Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More

Publisher / Amazon
2019
“Deep Learning From First Principles”
In vectorized Python, R and Octave

Amazon
2018
“Deep Learning through Sparse and Low-Rank Modeling”


Publisher / Amazon
2019
“Deep Learning with Python”
A Hands-on Introduction

Publisher / Amazon
2017
“Deep Reinforcement Learning for Wireless Networks”


Publisher / Amazon
2019
“Demand Forecasting for Inventory Control”


Publisher / Amazon
2015
“Descriptive Data Mining”


Publisher / Amazon
2017
“Designing with Data”
Improving the User Experience with A/B Testing

Publisher / Amazon
2017
“Deterministic Global Optimization”
An Introduction to the Diagonal Approach

Publisher / Amazon
2017
“Developing Analytic Talent: Becoming a Data Scientist”
The definitive job search and preparation guide for data scientists

Publisher / Amazon
2014
“Developing Bots with Microsoft Bots Framework”
Create Intelligent Bots using MS Bot Framework and Azure Cognitive Servic

Publisher / Amazon
2018
“Developments and Advances in Intelligent Systems and Applications”


Publisher / Amazon
2017
“Dictionary Learning Algorithms and Applications”


Publisher / Amazon
2018
“Diffuse Algorithms for Neural and Neuro-Fuzzy Networks”
With Applications in Control Engineering and Signal Processing

Publisher / Amazon
2017
“Diffusion in Social Networks”


Publisher / Amazon
2015
“Discrete Choice Analysis”
Theory and Application to Travel Demand

Publisher / Amazon
2018
“Discrete Data Analysis with R”
Visualization and Modeling Techniques for Categorical and Count Data

Publisher / Amazon
2015
“Discrete Optimization in Architecture”
Extremely Modular Systems

Publisher / Amazon
2016
“Discriminative Learning in Biometrics”


Publisher / Amazon
2016
“Disk-Based Algorithms for Big Data”


Publisher / Amazon
2016
“Disruptive Analytics”
Charting Your Strategy for Next-Generation Business Analytics

Publisher / Amazon
2016
“Docker for Data Science”
Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server

Publisher / Amazon
2017
“Doing Data Science”


Publisher / Amazon
2013
“Dynamic Data Analysis”
Modeling Data with Differential Equations

Publisher / Amazon
2017
“Effective CRM using Predictive Analytics”


Publisher / Amazon
2016
“Effizienzanalyse von Dienstleistungsproduktionen”
Eine Data Envelopment Analysis unter Berücksichtigung stochastischer externer Faktoren

Publisher / Amazon
2016
“Elements of Nonlinear Time Series Analysis and Forecasting”


Publisher / Amazon
2016
“Embedded Deep Learning”
Algorithms, Architectures and Circuits for Always-on Neural Network Processing

Publisher / Amazon
2019
“Empirical Approach to Machine Learning”


Publisher / Amazon
2019
“Encyclopedia of Algorithms”


Publisher / Amazon
2016
“Encyclopedia of Algorithms”


Publisher / Amazon
2016
“Encyclopedia of Distances”


Publisher / Amazon
2016
“Encyclopedia of Machine Learning”


Publisher / Amazon
2011
“Encyclopedia of Machine Learning and Data Mining”


Publisher / Amazon
2017
“Encyclopedia of Machine Learning and Data Mining”


Publisher / Amazon
2017
“Encyclopedia of Social Network Analysis and Mining”


Publisher / Amazon
2018
“Encyclopedia of Social Network Analysis and Mining”
(ESNAM)

Publisher / Amazon
2014
“Enhanced Machine Learning and Data Mining Methods for Analysing Large Hybrid Electric Vehicle Fleets based on Load Spectrum Data”


Publisher / Amazon
2018
“Ensemble Methods in Data Mining”
Improving Accuracy Through Combining Predictions

Publisher / Amazon
2010
“Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction”


Publisher / Amazon
2018
“Entertainment Science”
Data Analytics and Practical Theory for Movies, Games, Books, and Music

Publisher / Amazon
2019
“Environmental Data Analysis”
Methods and Applications

Publisher / Amazon
2016
“Environmental Data Analysis”
Methods and Applications

Publisher / Amazon
2017
“Essentials of Time Series for Financial Applications”


Publisher / Amazon
2018
“Event Mining”
Algorithms and Applications

Publisher / Amazon
2015
“Evolutionary Algorithms and Neural Networks”
Theory and Applications

Publisher / Amazon
2019
“Evolutionary Algorithms for Food Science and Technology”


Publisher / Amazon
2017
“Evolutionary and Swarm Intelligence Algorithms”


Publisher / Amazon
2019
“Evolutionary Computation and Complex Networks”


Publisher / Amazon
2019
“Evolutionary Multi-Agent Systems”
From Inspirations to Applications

Publisher / Amazon
2017
“Examples in Parametric Inference with R”


Publisher / Amazon
2016
“Experience Management”
Foundations, Development Methodology and Internet-Based Applications

Publisher / Amazon
2002
“Explainable and Interpretable Models in Computer Vision and Machine Learning”


Publisher / Amazon
2018
“Exploratory Multivariate Analysis by Example Using R”


Publisher / Amazon
2017
“Exploring Neural Networks with C#”


Publisher / Amazon
2014
“Extending the Linear Model with R”
Generalized Linear, Mixed Effects and Nonparametric Regression Models

Publisher / Amazon
2016
“Extracting Knowledge from Time Series”
An Introduction to Nonlinear Empirical Modeling

Publisher / Amazon
2010
“Extremal Optimization”
Fundamentals, Algorithms, and Applications

Publisher / Amazon
2016
“Extreme Value Distributions”


Publisher / Amazon
2016
“Fault-Tolerant Search Algorithms”
Reliable Computation with Unreliable Information

Publisher / Amazon
2013
“Feature Engineering for Machine Learning”
Principles and Techniques for Data Scientists

Publisher / Amazon
2018
“Feature Extraction, Construction and Selection”
A Data Mining Perspective

Publisher / Amazon
1998
“Feature Extraction: Foundations and Applications”


Publisher / Amazon
2006
“Feature Selection for High-Dimensional Data”


Publisher / Amazon
2016
“Federal Data Science”
Transforming Government and Agricultural Policy Using Artificial Intelligence

Publisher / Amazon
2017
“Finding out about”
A cognitive perspective on Search Engine Technology and the WWW

Amazon
2001
“Finite Mathematics”
Models and Applications

Publisher / Amazon
2015
“Flexible Imputation of Missing Data”


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2018
“Flexible Regression and Smoothing”
Using GAMLSS in R

Publisher / Amazon
2017
“Flood Forecasting Using Machine Learning Methods”


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2019
“Forecast Error Correction using Dynamic Data Assimilation”


Publisher / Amazon
2016
“Forecasting”
An Essential Introduction

Publisher / Amazon
2019
“Forecasting with the Theta Method”
Theory and Applications

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2019
“Formal Concept Analysis of Social Networks”


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2017
“Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering”


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2016
“Foundations of Data Science”
A Practical Introduction to Data Science with Python

Publisher / Amazon
2020
“Foundations of Predictive Analytics”


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2012
“Fourier Analysis of Economic Phenomena”


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2018
“Frameworks for Distributed Big Data Processing”
A Comparison in the Domain of Predictive Maintenance

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2018
“Fraud Data Analytics Methodology”
The Fraud Scenario Approach to Uncovering Fraud in Core Business Systems

Publisher / Amazon
2017
“From Basic Survival Analytic Theory to a Non-Standard Application”


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2017
“From Curve Fitting to Machine Learning”
An Illustrative Guide to Scientific Data Analysis and Computational Intelligence

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2016
“From Data to Decision”
A Handbook for the Modern Business Analyst

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2019
“From Human Attention to Computational Attention”
A Multidisciplinary Approach

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2018
“From Social Data Mining and Analysis to Prediction and Community Detection”


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2017
“Functional and Shape Data Analysis”


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2016
“Functional Data Analysis”


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2005
“Fundamental Issues of Artificial Intelligence”


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2016
“Fundamentals of Big Data Network Analysis for Research and Industry”


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2016
“Fundamentals of Clinical Data Science”


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2019
“Fundamentals of Database Indexing and Searching”


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2016
“Fundamentals of Deep Learning”
Designing Next-Generation Machine Intelligence Algorithms

Publisher / Amazon
2017
“Fundamentals of Machine Learning for Predictive Data Analytics”
Algorithms, Worked Examples, and Case Studies

Publisher / Amazon
2015
“Fundamentals of Optimization”
Methods, Minimum Principles, and Applications for Making Things Better

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2018
“Fundamentals of Predictive Text Mining”


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2015
“Fuzziness in Information Systems”
How to Deal with Crisp and Fuzzy Data in Selection, Classification, and Summarization

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2016
“Fuzzy Logic Augmentation of Neural and Optimization Algorithms”
Theoretical Aspects and Real Applications

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2018
“Fuzzy Machine Learning”
Advanced Approaches to Solve Optimization Problems

Publisher
2019
“Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration”


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2005
“Fuzzy Sets, Rough Sets, Multisets and Clustering”


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2017
“Fuzzy Technology”
Present Applications and Future Challenges

Publisher / Amazon
2016
“Gems of Combinatorial Optimization and Graph Algorithms”


Amazon
2015
“Generalizations of Fuzzy Information Measures”


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2016
“Generalized Additive Models”
An Introduction with R

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2017
“Generalized Connectivity of Graphs”


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2016
“Generalized Low Rank Models”


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2016
“Generalized Principal Component Analysis”


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2016
“Generative Adversarial Networks Projects”
Build next-generation generative models using TensorFlow and Keras

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2018
“Generative Deep Learning”
Teaching Machines to Paint, Write, Compose, and Play

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2019
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2017
“Genetic Algorithms in Java Basics”


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2015
“Genetic Programming Theory and Practice XIII”


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2017
“Genetic Programming Theory and Practice XVI”


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2019
“Genome Data Analysis”


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2018
“Granular Computing Based Machine Learning”
A Big Data Processing Approach

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2018
“Granular-Relational Data Mining”
How to Mine Relational Data in the Paradigm of Granular Computing?

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2017
“Graph Algorithms”
Practical Examples in Apache Spark and Neo4j

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2019
“Graph Analysis and Visualization”
Discovering Business Opportunity in Linked Data

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2015
“Graph-Based Social Media Analysis”


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2015
“Graph-Powered Machine Learning”


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2019
“Grey Data Analysis”
Methods, Models and Applications

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2017
“Grokking Deep Learning”


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2019
“Grouping Genetic Algorithms”
Advances and Applications

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2016
“Guide to Competitive Programming”
Learning and Improving Algorithms Through Contests

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2017
“Guide to Convolutional Neural Networks”
A Practical Application to Traffic-Sign Detection and Classification

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2017
“Guide to Data Analytics”


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2018
“Guide to Intelligent Data Analysis”
How to Intelligently Make Sense of Real Data

Publisher / Amazon
2010
“Hadoop”
The Definitive Guide

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2012
“Handbook of Approximate Bayesian Computation”


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2018
“Handbook of Big Data”


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2016
“Handbook of Big Data Analytics”


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2018
“Handbook of Convex Optimization Methods in Imaging Science”


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2017
“Handbook of Deep Learning Applications”


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2019
“Handbook of Discrete-Valued Time Series”


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2015
“Handbook of Graphical Models”


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2018
“Handbook of Heuristics”


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2018
“Handbook of Item Response Theory”
Volume One: Models

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2016
“Handbook of Metaheuristics”


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2019
“Handbook of Metaheuristics”


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2010
“Handbook of Missing Data Methodology”


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2014
“Handbook of Mixed Membership Models and Their Applications”


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2014
“Handbook of Model Checking”


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2018
“Handbook of Model Predictive Control”


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2019
“Handbook of Neural Computation”


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2017
“Handbook of Operations Analytics Using Data Envelopment Analysis”


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2016
“Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering”


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2018
“Handbook of Robust Low-Rank and Sparse Matrix Decomposition”
Applications in Image and Video Processing

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2016
“Handbook of Signal Processing Systems”


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2018
“Handbook of Statistical Analysis and Data Mining Applications”
2nd Edition

Publisher / Amazon
2017
“Handbook of Statistical Analysis and Data Mining Applications”


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2009
“Handbook of Statistical Methods and Analyses in Sports”


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2016
“Handbook of Survival Analysis”


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2013
“Handbook of Uncertainty Quantification”


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2017
“Hands-On Machine Learning with Scikit-Learn and TensorFlow”
Concepts, Tools, and Techniques for Building Intelligent Systems

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2017
“Hands-On Unsupervised Learning Using Python”
How to Build Applied Machine Learning Solutions from Unlabeled Data

Publisher / Amazon
2019
“Health Informatics Data Analysis”
Methods and Examples

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2017
“Healthcare Analytics”
From Data to Knowledge to Healthcare Improvement

Publisher / Amazon
2016
“Healthcare Data Analytics”


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2015
“Heuristic Search”
The Emerging Science of Problem Solving

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2017
“Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling”


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2016
“Hidden Markov Models for Time Series”
An Introduction Using R

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2016
“Hidden Semi-Markov Models”
Theory, Algorithms and Applications

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2015
“High Performance Data Mining and Big Data Analytics”
The Story of Insight from Big Data

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2014
“High-Utility Pattern Mining”
Theory, Algorithms and Applications

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2019
“Human Activity Recognition and Prediction”


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2016
“Human Re-Identification”


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2016
“Hybrid Intelligence for Social Networks”


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2018
“Hybrid Metaheuristics for Image Analysis”


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2018
“Hyper-lattice Algebraic Model for Data Warehousing”


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2016
“Independent Random Sampling Methods”


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2018
“Inference for Heavy-Tailed Data”
Applications in Insurance and Finance

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2017
“Information Fusion for Cyber-Security Analytics”


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2016
“Infrastruktur für ein Data Mining Design Framework”
Eine Untersuchung mit Fallbeispielen

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2018
“Insight into Fuzzy Modeling”


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2016
“Intelligent City Evaluation System”


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2018
“Intelligent Computing Systems”
Emerging Application Areas

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2016
“Intelligent Data Analysis”
An Introduction

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2006
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Trends and Applications

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2018
“Intelligent Techniques for Data Science”


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2016
“Intelligent Transportation Systems”
Dependable Vehicular Communications for Improved Road Safety

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2016
“Interpretability of Computational Intelligence-Based Regression Models”


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2015
“Interval-valued Methods in Classifications and Decisions”


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2019
“Introduction to Artificial Intelligence”


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2017
“Introduction to Artificial Intelligence”


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2016
“Introduction to Bayesian Statistics”


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2016
“Introduction to Data Science”
A Python Approach to Concepts, Techniques and Applications

Publisher / Amazon
2017
“Introduction to Deep Learning”
From Logical Calculus to Artificial Intelligence

Publisher / Amazon
2018
“Introduction to Deep Learning Using R”
A Step-by-Step Guide to Learning and Implementing Deep Learning Models using R

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2017
“Introduction to Learning Classifier Systems”


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2017
“Introduction to modern Time Series Analysis”


Publisher / Amazon
2008
“Introduction to Nature-Inspired Optimization”


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2017
“Introduction to Nonparametric Statistics for the Biological Sciences Using R”


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2016
“Introduction to Probability with Statistical Applications”


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2016
“Introduction to Scientific Computing and Data Analysis”


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2016
“Introduction to Statistical Analysis of Laboratory Data”


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2016
“Introduction to Statistical Machine Learning”


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2015
“Introduction to the Modeling and Analysis of Complex Systems”


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2015
“Introduction to Time Series and Forecasting”


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2016
“Introduction to Time Series Forecasting With Python”


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2017
“Issues in the Use of Neural Networks in Information Retrieval”


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2017
“Iterative Learning Control for Multi-agent Systems Coordination”


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2017
“Java Data Mining”
Strategy, Standard, and Practice. A Practical Guide for Architecture, Design, and Implementation

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2006
“Jaya”
An Advanced Optimization Algorithm and its Engineering Applications

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2019
“Joint Modeling of Longitudinal and Time-to-Event Data”


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2016
“Künstliche Intelligenz”


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2004
“Kalman Filtering”
with Real-Time Applications

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2017
“Keras to Kubernetes”
The Journey of a Machine Learning Model to Production

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2019
“Kernel Mean Embedding of Distributions”
A Review and Beyond

Publisher / Amazon
2017
“Knowledge Transfer between Computer Vision and Text Mining”
Similarity-based Learning Approaches

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2016
“Large-Scale and Distributed Optimization”


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2018
“Large-Scale Graph Processing Using Apache Giraph”


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2017
“Lasso-MPC – Predictive Control with 1-Regularised Least Squares”


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2016
“Learning Analytics”
Measurement Innovations to Support Employee Development

Publisher / Amazon
2016
“Learning Analytics in R with SNA, LSA, and MPIA”


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2016
“Learning Systems”
From Theory to Practice

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2018
“Learning TensorFlow”
A Guide to Building Deep Learning Systems

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2017
“Lecture Notes in Real-Time Intelligent Systems”


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2018
“Lifelong Machine Learning”


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2018
“Likelihood-Free Methods for Cognitive Science”


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2018
“Linear Algebra and Learning from Data”


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2019
“Linear and Nonlinear Optimization”


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2017
“Linear and Nonlinear Programming”


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2016
“Linear Programming”
Foundations and Extensions

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2014
“Linear Regression”


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2017
“Link Prediction in Social Networks”
Role of Power Law Distribution

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2016
“Logistics, Supply Chain and Financial Predictive Analytics”
Theory and Practices

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2019
“Longitudinal Data Analysis”
Autoregressive Linear Mixed Effects Models

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2019
“Loss Data Analysis”


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2018
“Low-Rank Models in Visual Analysis”
Theories, Algorithms, and Applications

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2017
“Machine Intelligence”
Demystifying Machine Learning, Neural Networks and Deep Learning

Publisher / Amazon
2019
“Machine Intelligence and Big Data in Industry”


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2016
“Machine Learners”
Archaeology of a Data Practice

Publisher / Amazon
2017
“Machine Learning”
A Practical Approach on the Statistical Learning Theory

Publisher / Amazon
2018
“Machine Learning”
An overview with the help of R software

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2018
“Machine Learning”
Algorithms and Applications

Publisher / Amazon
2016
“Machine Learning”
A Concise Introduction

Publisher / Amazon
2018
“Machine Learning”
A Concise Introduction

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2018
“Machine Learning”
The Art and Science of Algorithms that Make Sense of Data

Publisher / Amazon
2012
“Machine Learning”
A Probabilistic Perspective

Publisher / Amazon
2012
“Machine Learning and AI for Healthcare”
Big Data for Improved Health Outcomes

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2019
“Machine Learning and Security”
Protecting Systems with Data and Algorithms

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2018
“Machine Learning for Audio, Image and Video Analysis”
Theory and Applications

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2015
“Machine Learning for Big Data Analyis”


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2018
“Machine Learning for Evolution Strategies”


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2016
“Machine Learning For Hackers”


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2012
“Machine Learning for Mobile”
Practical guide to building intelligent mobile applications powered by machine learning

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2019
“Machine Learning for Model Order Reduction”


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2018
“Machine Learning for the Quantified Self”
On the Art of Learning from Sensory Data

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2018
“Machine Learning in Complex Networks”


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2016
“Machine Learning in Python”
Essential Techniques for Predictive Analysis

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2019
“Machine Learning in Python”
Essential Techniques for Predictive Analysis

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2015
“Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video”


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2018
“Machine Learning Models and Algorithms for Big Data Classification”
Thinking with Examples for Effective Learning

Publisher / Amazon
2016
“Machine Learning Paradigms”
Advances in Data Analytics

Publisher / Amazon
2019
“Machine Learning Paradigms”
Artificial Immune Systems and their Applications in Software Personalization

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2016
“Machine Learning Paradigms”
Applications in Recommender Systems

Publisher / Amazon
2015
“Machine Learning Paradigms”
Theory and Application

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2019
“Machine Learning Risk Assessments in Criminal Justice Settings”


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2019
“Machine Learning Techniques for Online Social Networks”


Publisher
2019
“Machine Learning Using R”
With Time Series and Industry-Based Use Cases in R

Publisher / Amazon
2019
“Machine Learning Using R”


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2017
“Machine Learning with PySpark”
With Natural Language Processing and Recommender Systems

Publisher
2019
“Machine Learning with the Elastic Stack”
Expert techniques to integrate machine learning with distributed search and analytics.

Publisher / Amazon
2019
“Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment”


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2020
“Machine Scheduling to Minimize Weighted Completion Times”
The Use of the a-point

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2018
“Machine-learning Techniques in Economics”
New Tools for Predicting Economic Growth

Publisher / Amazon
2017
“Managing and Mining Graph Data”
Advances in Database Systems

Publisher / Amazon
2012
“Market Segmentation Analysis”
Understanding It, Doing It, and Making It Useful

Publisher / Amazon
2018
“Marketing Analytics”
Data-Driven Techniques with Microsoft Excel

Publisher / Amazon
2014
“Marketing Analytics”
A Practical Guide to Improving Consumer Insights Using Data Techniques

Publisher / Amazon
2017
“Mastering Data Analysis with R”
Gain clear insights into your data and solve real-world data science problems with R – from data munging to modeling and visualization

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2015
“Mastering Machine Learning Algorithms”


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2018
“Mastering Machine Learning with R”


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2015
“Mastering Text Mining with R”
Master text-taming techniques and build effective text-processing applications with R

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2016
“Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases”


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2018
“Mathematical Problems in Data Science”
Theoretical and Practical Methods

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2015
“MATLAB Deep Learning”
With Machine Learning, Neural Networks and Artificial Intelligence

Publisher / Amazon
2017
“MATLAB Machine Learning Recipes”
A Problem-Solution Approach

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2018
“Matrix and Tensor Factorization Techniques for Recommender Systems”


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2017
“Matrix-Based Introduction to Multivariate Data Analysis”


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2016
“Maximum-Entropy Networks”
Pattern Detection, Network Reconstruction and Graph Combinatorics

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2017
“Means in Mathematical Analysis”
Bivariate Means

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2017
“Measures of Complexity”
Festschrift for Alexey Chervonenkis

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2015
“Measuring and Analysing the Use of Ontologies”
A Semantic Framework for Measuring Ontology Usage

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2018
“Medical Decision Making”
A Health Economic Primer

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2017
“Meta-Analysis”
A Structural Equation Modeling Approach

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2015
“Meta-Analytic Structural Equation Modelling”


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2015
“Meta-heuristic and Evolutionary Algorithms for Engineering Optimization”


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2018
“Metaheuristics”


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2016
“Mining Latent Entity Structures”


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2015
“Mining Multimedia Documents”


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2017
“Mining the Social Web”


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2018
“Missing Data Analysis in Practice”


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2015
“Mixed Effects Models for the Population Approach”
Models, Tasks, Methods and Tools

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2014
“Mixed Intelligent Systems”
Developing Models for Project Management and Evaluation

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2018
“Mixture Model-Based Classification”


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2016
“Mobile Data Mining and Applications”


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2019
“Model Averaging”


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2019
“Model Predictive Control”
Approaches Based on the Extended State Space Model and Extended Non-minimal State Space Model

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2019
“Model-Free Prediction and Regression”
A Transformation-Based Approach to Inference

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2015
“Modeling Discrete Time-to-Event Data”


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2016
“Modeling Discrete-Event Systems with GPenSIM”
An Introduction

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2018
“Modeling Techniques in Predictive Analytics”
Business Problems and Solutions with R

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2013
“Modeling with Rules Using Semantic Knowledge Engineering”


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2018
“Modern Algorithms of Cluster Analysis”


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2019
“Modern Analysis of Customer Surveys”
with Applications using R

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2012
“Modern Bayesian Statistics in Clinical Research”


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2018
“Monte-Carlo Simulation-Based Statistical Modeling”


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2017
“Movie Analytics”
A Hollywood Introduction to Big Data

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2015
“Multicriteria Analysis in Agriculture”
Current Trends and Recent Applications

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2018
“Multicriteria and Clustering”
Classification Techniques in Agrifood and Environment

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2017
“Multimedia Content Analysis”


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2016
“Multimodal Analysis of User-Generated Multimedia Content”


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2017
“Multimodal Optimization by Means of Evolutionary Algorithms”


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2015
“Multiobjective Linear and Integer Programming”


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2016
“Multiobjective Linear Programming”
An Introduction

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2016
“Multi-Objective Optimization Problems”
Concepts and Self-Adaptive Parameters with Mathematical and Engineering Applications

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2017
“Multi-Period Trading via Convex Optimization”


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2017
“Multiple Criteria Decision Analysis”
State of the Art Surveys

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2016
“Multiple Criteria Decision Making by Multiobjective Optimization”


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2016
“Multiple Instance Learning”
Foundations and Algorithms

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2016
“Multivariable Dynamic Calculus on Time Scales”


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2016
“Multivariate Modelling of Non-Stationary Economic Time Series”


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2017
“Multivariate Survival Analysis and Competing Risks”


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2016
“Multivariate Time Series With Linear State Space Structure”


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2016
“Multiview Machine Learning”


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2019
“Multiview Machine Learning for Data Analysis”


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2019
“Nature Inspired Optimization Techniques for Image Processing Applications”


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2019
“Nature-Inspired Algorithms and Applied Optimization”


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2018
“Nature-Inspired Optimization Algorithms”


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2016
“Nature-Inspired Optimizers”
Theories, Literature Reviews and Applications

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2019
“Network Analysis Literacy”
A Practical Approach to the Analysis of Networks

Publisher / Amazon
2016
“Network Data Envelopment Analysis”
Foundations and Extensions

Publisher / Amazon
2016
“Network Role Mining and Analysis”


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2017
“Network Traffic Anomaly Detection and Prevention”
Concepts, Techniques, and Tools

Publisher / Amazon
2017
“Neural Network Driven Artificial Intelligence”
Decision Making Based on Fuzzy Logic

Publisher / Amazon
2017
“Neural Networks and Deep Learning”
A Textbook

Publisher / Amazon
2018
“Neural Networks and Statistical Learning”


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2014
“New Approaches in Intelligent Image Analysis”
Techniques, Methodologies and Applications

Publisher / Amazon
2016
“New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks”


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2016
“New Directions on Model Predictive Control”


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2019
“New Introduction to Multiple Time Series Analysis”


Publisher
2005
“Non-Convex Multi-Objective Optimization”


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2017
“Nonlinear Principal Component Analysis and Its Applications”


Publisher / Amazon
2016
“Nonlinear Regression Modeling for Engineering Applications: Modeling, Model Validation, and Enabling Design of Experiments”


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2016
“Non-negative Matrix Factorization Techniques”
Advances in Theory and Applications

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2016
“Nonsmooth Optimization and Its Applications”


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2019
“Novel Applications of Intelligent Systems”


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2016
“Numerical Methods”
Using MATLAB

Publisher / Amazon
2018
“Numerical Optimization”


Publisher / Amazon
2006
“Numerical Probability”
An Introduction with Applications to Finance

Publisher / Amazon
2018
“Online Algorithms for the Portfolio Selection Problem”


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2016
“Online Portfolio Selection”
Principles and Algorithms

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2015
“Open Problems in Optimization and Data Analysis”


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2018
“Operational Modal Analysis”
Modeling, Bayesian Inference, Uncertainty Laws

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2017
“Operators for Similarity Search”
Semantics, Techniques and Usage Scenarios

Publisher / Amazon
2015
“Optimization and Approximation”


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2017
“Optimization and Decision Support Systems for Supply Chains”


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2017
“Optimization by GRASP”
Greedy Randomized Adaptive Search Procedures

Publisher / Amazon
2016
“Optimization in Engineering: Models and Algorithms”
Models and Algorithms

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2017
“Optimization of Energy Supply Systems”
Modelling, Programming and Analysis

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2019
“Outlier Analysis”


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2017
“Outlier Analysis”


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2017
“Outlier Detection: Techniques and Applications”
A Data Mining Perspective

Publisher / Amazon
2019
“Outlier Ensembles”
An Introduction

Publisher / Amazon
2017
“Parallel Computing for Data Science”
With Examples in R, C++ and CUDA

Publisher / Amazon
2015
“Parallelism in Matrix Computations”


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2015
“Partial Least Squares Structural Equation Modeling”
Recent Advances in Banking and Finance

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2018
“Partitional Clustering Algorithms”


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2014
“Pattern Classification of Biomedical Image Time-Series”
Computer Aided Diagnosis

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2017
“Pattern Mining with Evolutionary Algorithms”


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2016
“Patterns of Scalable Bayesian Inference”
Foundations and Trends in Machine Learning

Publisher / Amazon
2016
“Pedometrics”


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2018
“People Analytics in the Era of Big Data”
Changing the Way You Attract, Acquire, Develop, and Retain Talent

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2016
“Perceptrons”
Reissue Of The 1988 Expanded Edition With A New Foreword By Léon Bottou

Publisher / Amazon
2017
“Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models”
Theory and Applications

Publisher / Amazon
2019
“Perspectives on Data Science for Software Engineering”


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2016
“Plan Prediction”
Which Policy is Preferred by Which People?

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2017
“Point Processes for Reliability Analysis”
Shocks and Repairable Systems

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2019
“Point Processes for Reliability Analysis”
Shocks and Repairable Systems

Publisher / Amazon
2018
“Post, Mine, Repeat”
Social Media Data Mining Becomes Ordinary

Publisher / Amazon
2016
“Practical Automated Machine Learning on Azure”
sing AutoML to Build and Deploy Intelligent Solutions

Publisher / Amazon
2019
“Practical Data Science”
A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets

Publisher / Amazon
2018
“Practical Graph Analytics with Apache Giraph”


Publisher / Amazon
2015
“Practical Guide to Logistic Regression”


Publisher / Amazon
2015
“Practical Guide To Principal Component Methods in R”


Publisher / Amazon
“Practical Hive”
A Guide to Hadoop’s Data Warehouse System

Publisher / Amazon
2016
“Practical Machine Learning and Image Processing”
For Facial Recognition, Object Detection, and Pattern Recognition Using Python

Publisher / Amazon
2019
“Practical Recommender Systems”


Publisher / Amazon
2019
“Pragmatic AI”
An Introduction to Cloud-Based Machine Learning

Publisher / Amazon
2018
“Predicting Stock Returns”
Implications for Asset Pricing

Publisher / Amazon
2018
“Prediction and Inference from Social Networks and Social Media”


Publisher / Amazon
2017
“Predictive Analytics for Marketers”
Using Data Mining for Business Advantage

Publisher / Amazon
2018
“Predictive Analytics, Data Mining and Big Data”
Myths, Misconceptions and Methods

Publisher / Amazon
2014
“Predictive Data Mining Models”


Publisher / Amazon
2016
“Predictive HR Analytics”
Mastering the HR Metric

Publisher / Amazon
2019
“Predictive HR Analytics”
Mastering the HR Metric

Publisher / Amazon
2016
“Predictive Maintenance in Dynamic Systems”
Advanced Methods, Decision Support Tools and Real-World Applications

Publisher / Amazon
2019
“Principal Component Analysis Networks and Algorithms”


Publisher / Amazon
2017
“Principal Component and Correspondence Analyses Using R”


Publisher / Amazon
2018
“Principal Component Regression for Crop Yield Estimation”


Publisher / Amazon
2016
“Principles of Data Mining”


Publisher / Amazon
2016
“Pro Hadoop Data Analytics”
Designing and Building Big Data Systems using the Hadoop Ecosystem

Publisher / Amazon
2016
“Probabilistic Approaches to Recommendations”
Synthesis Lectures on Data Mining and Knowledge Discovery

Publisher / Amazon
2014
“Probabilistic Cellular Automata”
Theory, Applications and Future Perspectives

Publisher / Amazon
2018