Learn how to design, develop, deploy and iterate on production-grade ML applications.

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

🔊 Text-Prompted Generative Audio Model

The fastai deep learning library

Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable…

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

🤖 💬 Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)

A scikit-learn compatible neural network library that wraps PyTorch

Simple tutorials using Google's TensorFlow Framework

fast.ai Courses

From the basics to slightly more interesting applications of Tensorflow

Notebooks for learning deep learning

The 3rd edition of course.fast.ai

Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained

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

Probabilistic reasoning and statistical analysis in TensorFlow

Repo for the Deep Learning Nanodegree Foundations program.

Fast and flexible AutoML with learning guarantees.

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

Structured state space sequence models

A simple notebook demonstrating prompt-based music generation via Mubert API

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

A replica of the AlphaZero methodology for deep reinforcement learning in Python

1st place solution

Instructional notebooks on music information retrieval.

Videos, notes and experiments to understand deep learning

Tools to train a generative model on arbitrary audio samples

Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.