Python Machine Learning Resources

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Microsoft Machine Learning for Apache Spark MMLSpark is an ecosystem of tools aimed towards expanding the distributed computing framework Apache Spark

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

🔬 A curated list of awesome machine learning strategies & tools in financial market.

SageMaker Python SDK SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the S

Graph-based CTR prediction This is a repository designed for graph-based CTR prediction methods, it includes our graph-based CTR prediction methods: F

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

A python toolbox/library for data mining on partially-observed time series, supporting tasks of forecasting/imputation/classification/clustering on incomplete multivariate time series with missing values.

Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.

ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. It has a simple, flexible syntax, is cloud and tool agnostic, and has interfaces/abstractions that are catered towards ML workflows.

Interpretable Machine Learning with Python, published by Packt

Machine care An simple python script to take care of simple maintenance tasks fo

Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear

Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis

Model Factory Machine learning today is powering many businesses today, e.g., search engine, e-commerce, news or feed recommendation. Training high qu

Machine Learning Visualization Tools A single Python file with some tools for visualizing machine learning in the terminal. This demo is composed of t

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm

Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext

LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is implemented based on PyTorch, and includes all the necessary steps or components related to traffic prediction into a systematic pipeline.

Python package for probability density function fitting of univariate distributions of non-censored data

Azure MLOps (v2) solution accelerator Welcome to the MLOps (v2) solution accelerator repository! This project is intended to serve as the starting poi

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe

The collaboration platform for Machine Learning MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine

Prophet: Automatic Forecasting Procedure Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends ar

Price-Predictor Ml based project which uses regression technique to predict the price. I have used various regression models and finds the model with

Mesh TensorFlow - Model Parallelism Made Easier Introduction Mesh TensorFlow (mtf) is a language for distributed deep learning, capable of specifying

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API.

Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Currently 6 reports are available.

Using python and scikit-learn to make stock predictions

Apache SINGA Distributed deep learning system http://singa.apache.org Quick Start Installation Examples Issues JIRA tickets Code Analysis: Mailing Lis

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2021 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

Interactive Parallel Computing with IPython ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scr

Made With ML Applied ML · MLOps · Production Join 30K+ developers in learning how to responsibly deliver value with ML. 🔥 Among the top MLOps reposit

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Graphsignal is a machine learning model monitoring platform. It helps ML engineers, MLOps teams and data scientists to quickly address issues with data and models as well as proactively analyze model performance and availability.

ND DIAL: Imbalanced Algorithms Minimalist Python-based implementations of algorithms for imbalanced learning. Includes deep and representational learn

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

TensorFlowOnSpark TensorFlowOnSpark brings scalable deep learning to Apache Hadoop and Apache Spark clusters. By combining salient features from the T

BigDL: Distributed Deep Learning on Apache Spark What is BigDL? BigDL is a distributed deep learning library for Apache Spark; with BigDL, users can w

PyDLM Welcome to pydlm, a flexible time series modeling library for python. This library is based on the Bayesian dynamic linear model (Harrison and W

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and the A* Search (using the Manhattan Distance Heuristic)

Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

xarray-einstats Stats, linear algebra and einops for xarray ⚠️ Caution: This project is still in a very early development stage Installation To instal

sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

A Python library for choreographing your machine learning research.