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

A curated list of awesome deep long-tailed learning resources.

Improving adversarial robustness by a coupling rejection strategy

Repo for EchoVPR: Echo State Networks for Visual Place Recognition

This repository is all about spending some time the with the original problem posed by Minsky and Papert

Autoregressive Predictive Coding: An unsupervised autoregressive model for speech representation learning

Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

The official implementation of EIGNN: Efficient Infinite-Depth Graph Neural Networks (NeurIPS 2021)

Diabetes-Feature-Engineering - A machine learning model that can predict whether people have diabetes when their characteristics are specified

Demo code for ICCV 2021 paper "Sensor-Guided Optical Flow"

A framework for attentive explainable deep learning on tabular data

Code of our paper "Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning"

Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]

Masked regression code - Masked Regression

MiniSom is a minimalistic implementation of the Self Organizing Maps

Dynamic Environments with Deformable Objects (DEDO)

Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Datset)

Official PyTorch implementation of "RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on" (IJCAI-ECAI 2022)

Deep learning algorithms for muon momentum estimation in the CMS Trigger System

Code for paper "Document-Level Argument Extraction by Conditional Generation". NAACL 21'

Arch-Net: Model Distillation for Architecture Agnostic Model Deployment