Awesome Search - this is all about the (e-commerce, but not only) search and its awesomeness

Use Garry Tan's exact Claude Code setup: 23 opinionated tools that serve as CEO, Designer, Eng Manager, Release Manager, Doc Engineer, and QA

Scala Library/REPL for Machine Learning Research

Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)

Programming curricula

Practice your pandas skills!

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

"Deep Learning with TensorFlow" LiveLessons

Scientific time series and deep learning state of the art

A curated list of awesome things related to functional programming in Python.

https://www.meetup.com/Machine-Learning-Social-Hack-Nights/

A high-performance, purely-functional library for doing computational analysis and statistics over data in a type-safe way

Notes talking about the design and implementation of Apache Spark

A curated list of awesome Python asyncio frameworks, libraries, software and resources

learn-by-doing course/tutorial for functional programming on scala

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

"The mother of all demo apps" — Exemplary fullstack Medium.com clone powered by React, Angular, Node, Django, and many more

⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…

Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.

Python coded examples and documentation of machine learning algorithms.

📃 A list of practical projects that anyone can solve in any programming language.

Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

This repository contains all the material for the MLTrain NIPS workshop

Learn about Machine Learning and Artificial Intelligence

A curated list of awesome Deep Learning (DL) for Natural Language Processing (NLP) resources

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

Instructions and Guidelines for our Haskell Workshop/Study Group