TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

The fastai deep learning library

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

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

A clear, concise, simple yet powerful and efficient API for deep learning.

Deep Learning tutorials in jupyter notebooks.

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University

Over9000 optimizer

Code and example data for running Consensus Non-negative Matrix Factorization on single-cell RNA-Seq data

scikit-learn wrappers for Python fastText.

A Primer on Gaussian Processes for Regression Analysis (PyData NYC 2019)

Materials for the Presentation "A Crash Course in in Applied Linear Algebra"

devCellPy is a Python package designed for hierarchical multilayered classification of cells based on single-cell RNA-sequencing.