zikkat

awesome-python

An opinionated list of awesome Python frameworks, libraries, software and resources.

create-react-app

Set up a modern web app by running one command.

app-ideas

A Collection of application ideas which can be used to improve your coding skills.

tesseract

Tesseract Open Source OCR Engine (main repository)

Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

fastbook

The fastai book, published as Jupyter Notebooks

dolt

Dolt – Git for Data

deeplearning-models

A collection of various deep learning architectures, models, and tips

tsfresh

Automatic extraction of relevant features from time series:

sktime

A unified framework for machine learning with time series

pyprobml

Python code for "Probabilistic Machine learning" book by Kevin Murphy

feast

The Open Source Feature Store for Machine Learning

fastpages

An easy to use blogging platform, with enhanced support for Jupyter Notebooks.

scikit-llm

Seamlessly integrate LLMs into scikit-learn.

rlpyt

Reinforcement Learning in PyTorch

ThinkBayes

Code repository for Think Bayes.

evolution-strategies-starter

Code for the paper "Evolution Strategies as a Scalable Alternative to Reinforcement Learning"

python-opcua

LGPL Pure Python OPC-UA Client and Server

MLOpsPython

MLOps using Azure ML Services and Azure DevOps

submarine

Submarine is Cloud Native Machine Learning Platform.

opendigitaltwins-dtdl

Digital Twins Definition Language

ThinkBayes

Jupyter Notebooks derived from Allen Downey's book Think Bayes.

advance-bayesian-modelling-with-PyMC3

prog_models

The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.

PrognosticsModelLibrary

pydata-sf-2016-arima-tutorial

PyData San Francisco 2016 - ARIMA Tutorial

PrecisionWorkshop1_Prep

Preparation materials for CEAi Precision Workshop #1 on Bayesian modelling

deep-learning-repo

Implementation of Deep Learning architectures in TensorFlow and Keras

maintie

Maintenance Information Extraction (MaintIE)

azure-machine-learning-quickstarts

Quickstart labs that highlight specific features of Azure Machine Learning.