Category Archives: Books

Books worth a look

Book Memo: “Information-theoretic causal inference of lexical flow”

01 Sunday Dec 2019

Posted by in Books

≈ Leave a comment

This volume seeks to infer large phylogenetic networks from phonetically encoded lexical data and contribute in this way to the historical study of language varieties. The technical step that enables progress in this case is the use of causal inference algorithms. Sample sets of words from language varieties are preprocessed into automatically inferred cognate sets, and then modeled as information-theoretic variables based on an intuitive measure of cognate overlap. Causal inference is then applied to these variables in order to determine the existence and direction of influence among the varieties. The directed arcs in the resulting graph structures can be interpreted as reflecting the existence and directionality of lexical flow, a unified model which subsumes inheritance and borrowing as the two main ways of transmission that shape the basic lexicon of languages. A flow-based separation criterion and domain-specific directionality detection criteria are developed to make existing causal inference algorithms more robust against imperfect cognacy data, giving rise to two new algorithms. The Phylogenetic Lexical Flow Inference (PLFI) algorithm requires lexical features of proto-languages to be reconstructed in advance, but yields fully general phylogenetic networks, whereas the more complex Contact Lexical Flow Inference (CLFI) algorithm treats proto-languages as hidden common causes, and only returns hypotheses of historical contact situations between attested languages. The algorithms are evaluated both against a large lexical database of Northern Eurasia spanning many language families, and against simulated data generated by a new model of language contact that builds on the opening and closing of directional contact channels as primary evolutionary events. The algorithms are found to infer the existence of contacts very reliably, whereas the inference of directionality remains difficult. This currently limits the new algorithms to a role as exploratory tools for quickly detecting salient patterns in large lexical datasets, but it should soon be possible for the framework to be enhanced e.g. by confidence values for each directionality decision.

Book Memo: “Practical Time Series Analysis”

27 Friday Sep 2019

Posted by in Books

≈ Leave a comment

Prediction with Statistics and Machine Learning
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challenges in time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly.

Book Memo: “Machine Learning and Artificial Intelligence”

26 Thursday Sep 2019

Posted by in Books

≈ Leave a comment

This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspects of static and dynamic ML techniques. The forth part describes the practical applications where presented techniques can be applied. The fifth part introduces the user to some of the implementation strategies for solving real life ML problems.

Book Memo: “Neural Networks and Statistical Learning”

19 Thursday Sep 2019

Posted by in Books

≈ Leave a comment

2nd edition
This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing.

Book Memo: “Discrepancy Theory”

18 Wednesday Sep 2019

Posted by in Books

≈ Leave a comment

The contributions in this book focus on a variety of topics related to discrepancy theory, comprising Fourier techniques to analyze discrepancy, low discrepancy point sets for quasi-Monte Carlo integration, probabilistic discrepancy bounds, dispersion of point sets, pair correlation of sequences, integer points in convex bodies, discrepancy with respect to geometric shapes other than rectangular boxes, and also open problems in discrepany theory.

Book Memo: “Building Intelligent Cloud Applications”

17 Tuesday Sep 2019

Posted by in Books

≈ Leave a comment

Develop Scalable Models Using Serverless Architectures with Azure
Serverless computing is radically changing the way we build and deploy applications. With cloud providers running servers and managing machine resources, companies now can focus solely on the application’s business logic and functionality. This hands-on book shows experienced programmers how to build and deploy scalable machine learning and deep learning models using serverless architectures with Microsoft Azure. You’ll learn step-by-step how to code machine learning into your projects using Python and pre-trained models that include tools such as image recognition, speech recognition, and classification. You’ll also examine issues around deployment and continuous delivery including scaling, security, and monitoring.

Book Memo: “Statistical Learning of Complex Data”

11 Wednesday Sep 2019

Posted by in Books

≈ Leave a comment

This book of peer-reviewed contributions presents the latest findings in classification, statistical learning, data analysis and related areas, including supervised and unsupervised classification, clustering, statistical analysis of mixed-type data, big data analysis, statistical modeling, graphical models and social networks. It covers both methodological aspects as well as applications to a wide range of fields such as economics, architecture, medicine, data management, consumer behavior and the gender gap. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary.

Book Memo: “Learning Chaos Engineering”

09 Monday Sep 2019

Posted by in Books

≈ Leave a comment

Discovering and Overcoming System Weaknesses Through Experimentation
Most companies work hard to avoid costly failures, but in complex systems a better approach is to embrace and learn from them. Through chaos engineering, you can proactively hunt for evidence of system weaknesses before they trigger a crisis. This practical book shows software developers and system administrators how to plan and run successful chaos engineering experiments. System weaknesses go beyond your infrastructure, platforms, and applications to include policies, practices, playbooks, and people. Author Russ Miles explains why, when, and how to test systems, processes, and team responses using simulated failures on Game Days. You’ll also learn how to work toward continuous chaos through automation with features you can share across your team and organization.

Book Memo: “A Machine Learning Model for Improving Healthcare on Cloud Computing”

09 Monday Sep 2019

Posted by in Books

≈ Leave a comment

Recently, cloud computing gained an important role in healthcare services due to its ability to improve the healthcare performance. However, the optimal selection of virtual machines to process a medical request represents a big challenge. For that, it proposes a new model for healthcare based on cloud environment using Parallel Particle Swarm Optimization to optimize the virtual machines selection. In addition, a new model for chronic kidney disease diagnosis and prediction is proposed to measure the performance of our virtual machines model. The prediction model of chronic kidney disease is implemented using two consecutive techniques, which are linear regression and neural network.