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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
hill-a / stable-baselines
Forked from openai/baselinesA fork of OpenAI Baselines, implementations of reinforcement learning algorithms
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.
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.