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danrubins
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TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Learn how to design, develop, deploy and iterate on production-grade ML applications.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
A game theoretic approach to explain the output of any machine learning model.
The fastai book, published as Jupyter Notebooks
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
This repository contains implementations and illustrative code to accompany DeepMind publications
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
🤖 💬 Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
Image restoration with neural networks but without learning.
Visualizations for machine learning datasets
Code for Tensorflow Machine Learning Cookbook
An adversarial example library for constructing attacks, building defenses, and benchmarking both
Simple tutorials using Google's TensorFlow Framework
An annotated implementation of the Transformer paper.
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Efficient Image Captioning code in Torch, runs on GPU
Tacotron 2 - PyTorch implementation with faster-than-realtime inference
A collection of infrastructure and tools for research in neural network interpretability.
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
Probabilistic reasoning and statistical analysis in TensorFlow
Single Shot MultiBox Detector in TensorFlow
Language-Agnostic SEntence Representations
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Introduction to Deep Neural Networks with Keras and Tensorflow