Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

Last update: Dec 28, 2022

Overview

Google Cloud AI Developer Relations

This repository contains content produced by Google Cloud AI Developer Relations for machine learning and artificial intelligence. The content covers a wide spectrum from educational, training, and research, covering from novices, junior/intermediate to advanced.

The content has been designed both for self-learning, and for being incorporating into instructional material for universities, private coding schools, and professional training. Licensed as Apache 2.0 and CC-BY, organizations are free to integrate and customize the material into their curriculum.

The repository is organized by:

Directory	Description
`handbooks`	Google (FREE) PDF softcopy of handbooks - CC-BY 4.0 license (2019)
`books`	PDF softcopy of books - preview versions
`workshops`	workshops (presentation slides and code labs) - CC-BY 4.0 license (2019)
`notebooks`	notebooks for production-grade solutions
`zoo`	tf.keras model zoo (coded in idiomatic and composable design pattern) - Apache 2.0 license
`community labs`	Labs for community participation in research

Reviewers and Contributors

We thank the following for their reviews and contributions to the Idiomatic Programmer:

Google Cloud AI - Developer Relations

Andrew Ferlitsch
Noah Negrey
Yu-Han Liu
Shahin Saadati
Torry Yang
Gonzalo Gasca Meza
Amy Unruh
Martin Gorner
Brad Miro
Tianzi Cai
Sara Robinson
Puneith Kaul
Crystal Gomes

Other Current/Former Googlers

William Barret
Sharon Maher

Google Developer Experts (GDE)

Margaret Maynard-Reid / Seattle

ML Practioners

Hobson Lane
Enoch Tetteh
Bill Liu
Miklos Toth

Disclaimer

This is not an officially supported Google product.

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

Related tags

Overview

Google Cloud AI Developer Relations

Reviewers and Contributors

Disclaimer

Owner

Google Cloud Platform

The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"

Implementation of the famous Image Manipulation\Forgery Detector "ManTraNet" in Pytorch

Tensor-Based Quantum Machine Learning

This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees

SiT: Self-supervised vIsion Transformer

This repository contains datasets and baselines for benchmarking Chinese text recognition.

Source code for the ACL-IJCNLP 2021 paper entitled "T-DNA: Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adaptation" by Shizhe Diao et al.

Code for the CIKM 2019 paper "DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting".

Optical machine for senses sensing using speckle and deep learning

The spiritual successor to knockknock for PyTorch Lightning, get notified when your training ends

This is the code for Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning

Code for testing various M1 Chip benchmarks with TensorFlow.

A Lightweight Hyperparameter Optimization Tool 🚀

TalkNet 2: Non-Autoregressive Depth-Wise Separable Convolutional Model for Speech Synthesis with Explicit Pitch and Duration Prediction.

darija <-> english dictionary

This code is a near-infrared spectrum modeling method based on PCA and pls

2.86% and 15.85% on CIFAR-10 and CIFAR-100

Densely Connected Search Space for More Flexible Neural Architecture Search (CVPR2020)

A PyTorch implementation of "TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?"

Use unsupervised and supervised learning to predict stocks