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

Overview

License License

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.

Owner
Google Cloud Platform
Google Cloud Platform
A Closer Look at Structured Pruning for Neural Network Compression

A Closer Look at Structured Pruning for Neural Network Compression Code used to reproduce experiments in https://arxiv.org/abs/1810.04622. To prune, w

Bayesian and Neural Systems Group 140 Dec 05, 2022
[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets

[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets Introduction This repo contains the source code accompanying the paper: Well-tuned Sim

52 Jan 04, 2023
a spacial-temporal pattern detection system for home automation

Argos a spacial-temporal pattern detection system for home automation. Based on OpenCV and Tensorflow, can run on raspberry pi and notify HomeAssistan

Angad Singh 133 Jan 05, 2023
Data and analysis code for an MS on SK VOC genomes phenotyping/neutralisation assays

Description Summary of phylogenomic methods and analyses used in "Immunogenicity of convalescent and vaccinated sera against clinical isolates of ance

Finlay Maguire 1 Jan 06, 2022
Submission to Twitter's algorithmic bias bounty challenge

Twitter Ethics Challenge: Pixel Perfect Submission to Twitter's algorithmic bias bounty challenge, by Travis Hoppe (@metasemantic). Abstract We build

Travis Hoppe 4 Aug 19, 2022
Towhee is a flexible machine learning framework currently focused on computing deep learning embeddings over unstructured data.

Towhee is a flexible machine learning framework currently focused on computing deep learning embeddings over unstructured data.

1.7k Jan 08, 2023
QICK: Quantum Instrumentation Control Kit

QICK: Quantum Instrumentation Control Kit The QICK is a kit of firmware and software to use the Xilinx RFSoC to control quantum systems. It consists o

81 Dec 15, 2022
Pytorch implementation of the AAAI 2022 paper "Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification"

[AAAI22] Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification We point out the overlooked unbiasedness in long-tailed clas

PatatiPatata 28 Oct 18, 2022
This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is accepted to ICCV2021.

GMPQ: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation This is the pytorch implementation for the paper: Generalizable Mix

18 Sep 02, 2022
Learning Logic Rules for Document-Level Relation Extraction

LogiRE Learning Logic Rules for Document-Level Relation Extraction We propose to introduce logic rules to tackle the challenges of doc-level RE. Equip

41 Dec 26, 2022
以孤立语假设和宽度优先搜索为基础,构建了一种多通道堆叠注意力Transformer结构的斗地主ai

ddz-ai 介绍 斗地主是一种扑克游戏。游戏最少由3个玩家进行,用一副54张牌(连鬼牌),其中一方为地主,其余两家为另一方,双方对战,先出完牌的一方获胜。 ddz-ai以孤立语假设和宽度优先搜索为基础,构建了一种多通道堆叠注意力Transformer结构的系统,使其经过大量训练后,能在实际游戏中获

freefuiiismyname 88 May 15, 2022
DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors

DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors By Anargyros Chatzitofis, Dimitris Zarpalas, Stefanos Kollias

tofis 24 Oct 08, 2022
Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code

Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code.

Yasunori Shimura 7 Jul 27, 2022
GraPE is a Rust/Python library for high-performance Graph Processing and Embedding.

GraPE GraPE (Graph Processing and Embedding) is a fast graph processing and embedding library, designed to scale with big graphs and to run on both of

AnacletoLab 194 Dec 29, 2022
Cortex-compatible model server for Python and TensorFlow

Nucleus model server Nucleus is a model server for TensorFlow and generic Python models. It is compatible with Cortex clusters, Kubernetes clusters, a

Cortex Labs 14 Nov 27, 2022
An auto discord account and token generator. Automatically verifies the phone number. Works without proxy. Bypasses captcha.

JOIN DISCORD SERVER https://discord.gg/uAc3agBY FREE HCAPTCHA SOLVING API Discord-Token-Gen An auto discord token generator. Auto verifies phone numbe

3kp 271 Jan 01, 2023
This is an official source code for implementation on Extensive Deep Temporal Point Process

Extensive Deep Temporal Point Process This is an official source code for implementation on Extensive Deep Temporal Point Process, which is composed o

Haitao Lin 8 Aug 15, 2022
ICLR 2021 i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning

Introduction PyTorch code for the ICLR 2021 paper [i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning]. @inproceedings{lee2021i

Kibok Lee 68 Nov 27, 2022
Scripts used to make and evaluate OpenAlex's concept tagging model

openalex-concept-tagging This repository contains all of the code for getting the concept tagger up and running. To learn more about where this model

OurResearch 18 Dec 09, 2022
A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."

EfficientNet A PyTorch implementation of EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. [arxiv] [Official TF Repo] Implemen

AhnDW 298 Dec 10, 2022