The Memory layer for your AI apps

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.

Distributed ML Training and Fine-Tuning on Kubernetes

Style guides for Google-originated open-source projects

🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Code for the paper "Exploration by Random Network Distillation"

Modularized Implementation of Deep RL Algorithms in PyTorch

Experiments with Deep Learning

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

Soft Actor-Critic

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis

A tiny lib with pocket-sized implementations of machine learning models in NumPy, most of which will fit in a tweet.

Cassandra monitoring tool integrated with spring boot

Efficient Batched Reinforcement Learning in TensorFlow

An Open Source Machine Learning Framework for Everyone

A TensorFlow implementation of the Differentiable Neural Computer.

Python Data Science Handbook: full text in Jupyter Notebooks

Repo for the Deep Learning Nanodegree Foundations program.

fast.ai Courses

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

🌎 Simple and ready-to-use tutorials for TensorFlow

TensorFlow Tutorials with YouTube Videos

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.