• en-qai-sm
English multi-task CNN trained on OntoNotes. Assigns context-specific token vectors, POS tags, dependency parse and named entities.

• faircorels
FairCORELS, a modified version of CORELS to build fair and interpretable models. Welcome to FairCorels, a Python library for learning fair and interpretable models using the Certifiably Optimal RulE ListS (CORELS) algorithm!

• flexi-hash-embedding
PyTorch Extension Library of Optimized Scatter Operations. This PyTorch Module hashes and sums variably-sized dictionaries of features into a single fixed-size embedding. Feature keys are hashed, which is ideal for streaming contexts and online-learning such that we don’t have to memorize a mapping between feature keys and indices. Multiple variable-length features are grouped by example and then summed. Feature embeddings are scaled by their values, enabling linear features rather than just one-hot features.

• JLpy-utils-package
Custom methodes for various data science, computer vision, and machine learning operations in python

• kde-gpu
We implemented nadaraya waston kernel density and kernel conditional probability estimator using cuda through cupy. It is much faster than cpu version but it requires GPU with high memory.

• matchzoo-py
Facilitating the design, comparison and sharingof deep text matching models.

• naive-feature-selection
Naive Feature Selection. This package solves the Naive Feature Selection problem described in [the paper](https://…/1905.09884 ).

• pencilbox
A pencilbox for your Jupyter notebooks.

• pyAudioProcessing
Audio processing-feature extraction and building machine learning models from audio data.

• scrolldown
Keep long running notebook in jupyter scrolled to the bottom

• styletransfer
Transfer the style of one image to another using PyTorch

• tf-object-detection
A Thin Wrapper around Tensorflow Object Detection API for Easy Installation and Use. This is a thin wrapper around [Tensorflow Object Detection API](https://…/object_detection ) for easy installation and use. The original [installation procedure](https://…/installation.md ) contains multiple manual steps that make dependency management difficult. This repository creates a pip package that automate the installation so that you can install the API with a single pip install.

• titanfe
titan Data Flow Engine for Python

• trendet
trendet – is a Python package for trend detection on stock time series data

• twodlearn
Easy development of machine learning models

• tuesday
A python package for automisation. You can easily automize and most of the commands of system by your voice. By using this package u can easily build jarvis like programme, irrespective of your knowledge of coding. Easy voice commands to work with.

• cltkv1
Classical Language Toolkit

• predicode
Simulations and interface to analytical solutions of predictive coding

• allennlp-pvt-nightly
An open-source NLP research library, built on PyTorch.

• analytics-utils
Package with functions for data analytics

• data-view
Automated view of dataset

• dibb
A framework for Distributed Black-Box {optimization, search, algorithms}

• jiayan
The NLP toolkit designed for classical chinese.

• larrydata
Library of helper modules for common data tasks using AWS resources such as S3, SQS, MTurk and others. Library of utilities for common data tasks using AWS. While boto3 is a great interface for interacting with AWS services, it can be overly complex for data scientists and others who want to perform simple operations on data without worrying about API-specific interactions and parameters. Larrydata provides a simple wrapper for S3, MTurk, and other data-oriented services to let you focus on the data rather than syntax.

• MatchZoo-test
Facilitating the design, comparison and sharingof deep text matching models.

• proto-dist-ml
Prototype-based Machine Learning on Distance Data.

• telegram-botup
Library for development Telegram bots

• tensorflow-radam
RAdam implemented in Keras & TensorFlow

• testbook
A testing package using Jupyter Notebooks

• transformer-model
A Transformer model implementation in TensorFlow 2.0

• cellannotation
Package for annotating the data (e.g. cell data). This package provides functionalities to annotate data with labels based on the Mann-Whitney U test and Hypergeometric test. Currently, we provide examples of the fast annotation of gene expression data with the cell types based on marker genes.

• datalearn19intro
Helper code for DataLearn 2019 ML Intro Workshop.

• easy-keras
An easy wrapper around Keras models

• elastic-enterprise-search
An API client for Elastic Enterprise Search

• empyricalRMT
Eigenvalue unfolding and spectral observable computation. A python library for Random Matrix Theory eigenvalue unfolding and computation and plotting of spectral observables.

• fastax
A Jax based neural network library for research. fastax is a Deep Learning Library built on top of Google’s [JAX](https://…/jax ) that tries to facilitate doing research by providing a combination of JAX’s versatility with implementations of the most used neural networks layers and utilities.

• gdascore-mock
Tools for generating General Data Anonymity Scores (www.gda-score.org). This repo holds a variety of tools in support of the GDA Score Project (General Data Anonymity Score Project). The code here is still very much alpha, and little effort has gone into making it easy for others to install and use. The primary language is Python, and requires Python3.7 or later. API documentation for some of the tools can be found at https://…/.

• jupyterlab-celltests
Cell-by-cell tests for JupyterLab. `Celltests` is designed for writing tests for linearly executed notebooks. Its primary use is for unit testing reports.

• ml-studio
Machine Learning Algorithms

• paddle2onnx
is a toolkit for converting trained model to onnx from PaddlePaddle frameworks.

• pdfpug
Simple PDF Creator

• phyre
Benchmark for PHYsical Reasoning. It provides a set of physics puzzles in a simulated 2D world. Each puzzle has a goal state (e.g., *make the green ball touch the blue wall*) and an initial state in which the goal is not satisfied (see the figure below). A puzzle can be solved by placing one or more new bodies in the environment such that when the physical simulation is run the goal is satisfied. An agent playing this game must solve previously unseen puzzles in as few attempts as possible.

• pysampling
Multi-Objective Optimization in Python

• python-aws-ssm
Python package that interfaces with AWS System Manager

• Resemblyzer
Analyze and compare voices with deep learning

• soio
A single objective intelligent optimization package

• textgetter
A python package for extracting text from PDF/TIF/JPG/PNG files

• jcopdl
J.COp DL is a deep Learning package to complement pytorch workflow. It includes pytroch callbacks and metrics.

• latent-dirichlet-allocation
Latent-dirichlet-allocation

• TensorKit


• TensorKit-plottools


• TensorKit-tools


• torchtrainer
Focus on building and optimizing pytorch models not on training loops. PyTorch model training made simpler without loosing control. Focus on optimizing your model! Concepts are heavily inspired by the awesome project [torchsample](https://…/torchsample ) and [Keras](https://…/keras ). Further, besides applying Epoch Callbacks it also allows to call Callbacks every time after a specific number of batches passed (iterations) for long epoch durations.

• TorchVC
Voice Conversion in PyTorch

• abode
Python Environment and Package Manager

• dibbo
A framework for Distributed Black-Box Optimization

• jupyterlab-zenodo
A Jupyter Notebook extension which enables uploading to Zenodo from JupyterLab

• mlgen
MLGen is a tool which helps you to generate machine learning code with ease. MlGen is a tool which helps you to generate machine learning code with ease. MLGen uses a ‘.mlm’ file format which is a file with YML like syntax. This tool as of now supports keras and tensorflow2.0(not fully supported)

• naturalselection
An all-purpose pythonic genetic algorithm

• pyexlatex
Python Extends LaTeX – A High-Level Python API for Creating Latex Documents. This project is aimed at creating LaTeX documents using only Python, without directly writing LaTeX code. Rather than building a direct Python API to LaTeX, this package has its own, simpler API to creating documents.

• pysimrel
Simulating data from linear model data

• saattrupdan.darwin
An all-purpose pythonic genetic algorithm

• som-learn
Self-Organizing Map algorithm.

• sqlizer
Orchestration service for SQL only ETL workflows. In many cases you can use SQL only for ETL (extract/transform/load) pipelines relying on CTAS (create table as) queries and the builting import/export futures of your RDBMS or data warehouse software (eg. Redshift).

• textsense
TextSense.ai a Text analytics platform.

• torchmeta
Dataloaders for meta-learning in Pytorch. A collection of extensions and data-loaders for few-shot learning & meta-learning in [PyTorch](https://pytorch.org ). The package contains popular meta-learning benchmarks, fully compatible with both [`torchvision`](https://…/index.html ) and PyTorch’s [`DataLoader`](https://…/data.html#torch.utils.data.DataLoader ).

• cluster-over-sampling
Clustering based over-sampling.

• csdmpy
A python module for importing and exporting CSD model file-format. The `csdmpy` package is a Python support for the core scientific dataset (CSD) model file exchange-format. The package is based on the core scientific dataset (CSD) model which is designed as a building block in the development of a more sophisticated portable scientific dataset file standard. The CSD model is capable of handling a wide variety of scientific datasets both within and across disciplinary fields.

• fastrank
A set of learning-to-rank algorithms.

• lisc
Literature Scanner. LISC, or ‘literature scanner’ is a package for collecting and analyzing scientific literature. LISC acts as a wrapper and connector between available APIs, allowing users to collect data from and about scientific articles, and to do analyses on this data, such as performing automated meta-analyses.

• pylift
Python implementation of uplift modeling.

• pythonGraph
simple graphics in Python. pythonGraph is a simple graphics package for Python. It’s design is loosely descended from Adagraph and RAPTOR Graph. pythonGraph supports the creation of a graphics window, the display of simple geometric shapes, and simple user interactions using the mouse and keyboard.

• pytorch-transformers-pvt-nightly
Repository of pre-trained NLP Transformer models: BERT & RoBERTa, GPT & GPT-2, Transformer-XL, XLNet and XLM

• qubu
A Simple Database Query Builder

• rl-musician
Composition of music with reinforcement learning.

• shapeletpy
Time series classification Using Shapelets

• torch-radiate
Automatic deep learning research report generator

• torch-stethoscope
Automatic deep learning research report generator

• yahoo-finance-hdd
Download historical financial data from yahoo finance

• affnine-deltaleaf
Easy way to create MAP (Undirected Graph)and find shortest path from one Node to another.

• apai
ML & DL helper library. Helper library built on Tensorflow. Provides utility and helper functions for the machine and deep learning tasks.

• easyagents-v1
reinforcement learning for practitioners. Use EasyAgents if
• you are looking for an easy and simple way to get started with reinforcement learning
• you have implemented your own environment and want to experiment with it
• you want mix and match different implementations and algorithms

• ignis
Intuitive library for training neural nets in PyTorch. `ignis` is a high-level library that helps you write compact but full-featured training loops with metrics, early stops, and model checkpoints for deep learning library [PyTorch](https://pytorch.org ).

• rgxg
ReGular eXpression Generator

• robolab
Open source development tools for Robot Framework RPA developers

• smitter
HPC submission for deep learning.

• smoothfit
Smooth data fitting. Given experimental data, it is often desirable to produce a function whose values match the data to some degree. This package implements a robust approach to data fitting based on a minimization problem.

• tensorflow-gcp
TensorFlow for GCP. TensorFlow for GCP is a software library for high performance numerical computation based on TensorFlow. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.

• typecats
Structure unstructured data for the purpose of static type checking. In many web services it is common to consume or generate JSON or some JSON-like representation of data. JSON translates quite nicely to core Python objects such as dicts and lists. However, if your data is structured, it is nice to be able to work with it in a structured manner, i.e. with Python objects. Python objects give you better code readability, and in more recent versions of Python they are also capable of being statically type-checked with a tool like `mypy`.

• awkward1
Development of awkward 1.0, to replace scikit-hep/awkward-array in 2020.

• Azure-Sentinel-Utilities
AZURE SENTINEL NOTEBOOKS PYTHON TOOLS: This package is developed to support Azure Sentinel Notebooks. It is in an early preview stage so please provide feedback, report bugs, and suggets for new features.

• graphqt
Create Graph DataStructure. This is test library for the python which lets you create graph using some functions. This library will allow you to create undirected graphs and also provides some of the other functionalities. This library is for the beginner programmer who wants to get started at the programming with the graphs and want to visualize it easily. It is highly recommended to learn the actual code so that one can implement them without using this library at the interviews, and competition. This library was designed for the programmers who are studying graph currently. This will allow them to have the idea and brute force solution to them which they can further optimize.

• mk-tf-img-mod
Easy to use Image Learning Module for Tensorflow

• Multi-Template-Matching
Object-recognition in images using multiple templates. Multi-Template-Matching is a package to perform object-recognition in images using one or several smaller template images. The template and images should have the same bitdepth (8,16,32-bit) and number of channels (single/Grayscale or RGB). The main function `MTM.matchTemplates` returns the best predicted locations provided either a score_threshold and/or the expected number of objects in the image.

• TensorTrade
A reinforcement learning library for training, evaluating, and deploying robust trading agents with TF2.

• zw-flink
Apache Flink Python API. Apache Flink is an open source stream processing framework with the powerful stream- and batch-processing capabilities. Learn more about Flink at (https://flink.apache.org ) This packaging allows you to write Flink programs in Python, but it is currently a very initial version and will change in future versions.

• change_detection
package for detecting change in time-series data. Detects changes in time series using the R package gets (https://…/index.html ). Uses a combination of Google BigQuery and Python to query data, which is then fed to the R change detection code. Outputs a table containing results.

• gdascore
Tools for generating General Data Anonymity Scores (www.gda-score.org)

• gdascore-mock
Tools for generating General Data Anonymity Scores (www.gda-score.org)

• ingaia-gcloud
Python utility library for Google Cloud Platform

• py2store
Interfacing with stored data through python. Storage CRUD how and where you want it. List, read, write, and delete data in a structured data source/target, as if manipulating simple python builtins (dicts, lists), or through the interface **you** want to interact with, with configuration or physical particularities out of the way. Also, being able to change these particularities without having to change the business-logic code.

• vibra
An add-on to Tensorflow

• WordTreeGenerator
Package to generate word tree html

• xpath-parser
A xpath expression parser

• vrt-generator
creating vrt corpora

• across
Run Python code across different machines

• act-atmos
Package for working with atmospheric time series datasets

• blacksheep-outliers
A package for differential extreme values analysis

• dpy
A tool that automatically generates quality documentation for Python projects.

• enhanceml
An ML enhancement package to improve outcomes. enhanceml (Enhance Machine Learning model) is a Python library to enhance the prediction of model using various statistical technique. This contains various sub-models which can be fitted over data to predict outcome.

• galaxy2galaxy
Galaxy2Galaxy

• jupyterlab-hdf
A Jupyter Notebook server extension that provides APIs for fetching hdf5 contents and data. Built on h5py.

• kss
Split Korean text into sentences using heuristic algorithm.

• libsvm
Pre-built LibSVM packages for Python.

• MiTfAT
A python-based fMRI Analysis Tool.

• nbflow
A tool that supports one-button reproducible workflows with the Jupyter Notebook and Scons

• oats-power
OATS: Optimisation and Analysis Toolbox for Power Systems

• pflacco
An python interface to the R package flacco for computing ELA features.

• pypipes
Pipeline processing framework

• exceldriver
Tool for automating excel actions on Windows

• experimentlogger-jathr
Simple logger for Machine Learning experiments

• hip-data-tools
Common utility functions for data engineering usecases

• hmmkay
Discrete Hidden Markov Models with Numba

• liepa-tts
Python bindings for Lithuanian language synthesizer from LIEPA project

• matplot


• matrix-operations
various matrix operations

• megadictionary
A fully formatted dictionary for everything you’ll ever need.

• mothnet
Neural network modeled after the olfactory system of the hawkmoth

• PVPolyfit
A high-resolution multiple linear regression algorithm used to analyze PV output with a few inputs

• pyatlasclient
Apache Atlas Python Client

• rdilmarkdown
Markdown in Python.

• semvecpy
Semantic Vectors work in Python

• skymind-pipelines
pipelines: Deploy your machine learning experiments with Skymind Pipelines

• TensorFI-BinaryFI
A Binary fault injection tool for TensorFlow-based program

• text-normalization
A text normalization package

• torch-kerosene
Pytorch Framework For Medical Image Analysis

• veho
A helper for working with 1d & 2d array.

• Automagica
Robot for Automagica – Smart Robotic Process Automation

• experta
Expert Systems for Python

• jupyterlab-s3-browser
A Jupyter Notebook server extension which acts a proxy for the S3 API.

• labeledclusters
Python code for handling clusters of labeled, high-dimensional data

• pyneural
Library for brain modeling and machine learning in Python 3

• pypotree
Potree visualization for jypyter notebooks

• pytorch-transformers-nightly-unofficial
Repository of pre-trained NLP Transformer models: BERT, GPT & GPT-2, Transformer-XL, XLNet and XLM

• sparqlprog
Execute logic program queries against a remote SPARQL endpoint

• tipboard2.0
Tipboard – a flexible solution for creating your dashboards.

• autoviml
Automatically Build Variant Interpretable ML models fast!

• causalml
Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms

• cincoconfig
Universal configuration file parser

• completejourney-py
Data from R package completejourney

• contessa
Data-quality framework

• EasyModels
Command Line User Interface for finding pre-trained AI models

• liyc-hand-superset
A modern, enterprise-ready business intelligence web application

• liyc-superset
A modern, enterprise-ready business intelligence web application

• llp
Literary Language Processing (LLP): corpora, models, and tools for the digital humanities

• mlswarm
This package trains neural networks using swarm-like optimization algorithms

• multi-imbalance
Python package for tackling multiclass imbalance problems.

• pytorch-wrapper
PyTorchWrapper is a library that provides a systematic and extensible way to build, train, evaluate, and tune deep learning models using PyTorch. It also provides several ready to use modules and functions for fast model development.

• robustats
Robustats is a Python library for high-performance computation of robust statistical estimators.

• vtreat


• warp-rna
PyTorch bindings for CUDA-Warp Recurrent Neural Aligner

• bayesian-changepoint-detection
Some Bayesian changepoint detection algorithms

• censor-fix
A library for multiple imputaion of censored data

• copula
A python library for sampling and generating new Data points by multivariate Gaussian copulas.

• mrextractor
A library for binaries feature extraction

• recommender-system
Acuracy and Efficient Recommander System

• jupyterlab-nvdashboard
A JupyterLab extension for displaying dashboards of GPU usage.