Deep Learning for humans

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

🥇掘金翻译计划，可能是世界最大最好的英译中技术社区，最懂读者和译者的翻译平台：

TensorFlow code and pre-trained models for BERT

Clone a voice in 5 seconds to generate arbitrary speech in real-time

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

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

Deezer source separation library including pretrained models.

100-Days-Of-ML-Code中文版

📡 Simple and ready-to-use tutorials for TensorFlow

Open-Source Photo Management powered by Go and Google TensorFlow

Visualizer for neural network, deep learning, and machine learning models

ncnn is a high-performance neural network inference framework optimized for the mobile platform

Face recognition using Tensorflow

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 175 universities.

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Deep learning library featuring a higher-level API for TensorFlow.

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

Mapping a variable-length sentence to a fixed-length vector using BERT model