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

PyTorch code for the paper "FIERY: Future Instance Segmentation in Bird's-Eye view from Surround Monocular Cameras"

Easy to use Python camera interface for NVIDIA Jetson

Implementation for the paper: Invertible Denoising Network: A Light Solution for Real Noise Removal (CVPR2021).

Official code for our CVPR '22 paper "Dataset Distillation by Matching Training Trajectories"

Code for the paper "Unsupervised Contrastive Learning of Sound Event Representations", ICASSP 2021.

RP-GAN: Stable GAN Training with Random Projections

The Pytorch implementation for "Video-Text Pre-training with Learned Regions"

AOT (Associating Objects with Transformers) in PyTorch

Code for How To Create A Fully Automated AI Based Trading System With Python

PyTorch code to run synthetic experiments.

Invasive Plant Species Identification

GeoTransformer - Geometric Transformer for Fast and Robust Point Cloud Registration

Python scripts for performing road segemtnation and car detection using the HybridNets multitask model in ONNX.

🐦 Quickly annotate data from the comfort of your Jupyter notebook

Virtual hand gesture mouse using a webcam

Official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution"

Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"

PushForKiCad - AISLER Push for KiCad EDA

Code for the TASLP paper "PSLA: Improving Audio Tagging With Pretraining, Sampling, Labeling, and Aggregation".

Seq2seq - Sequence to Sequence Learning with Keras