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

Deep Learningmachine-learningdeep-learningkerasvggdcganautoencoderdensenetresnetkeras-tutorialssqueezenetinceptionresnextautomlmobilenetsiamese-networkshufflenetsenetxceptiontensorflow-keras
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
GitHub Repository
git《Self-Attention Attribution: Interpreting Information Interactions Inside Transformer》(AAAI 2021) GitHub:

Self-Attention Attribution This repository contains the implementation for AAAI-2021 paper Self-Attention Attribution: Interpreting Information Intera

60 Dec 29, 2022
On Evaluation Metrics for Graph Generative Models

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

13 Jan 07, 2023
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrai

Hugging Face 77.4k Jan 05, 2023
Official implementation of "Watermarking Images in Self-Supervised Latent-Spaces"

🔍 Watermarking Images in Self-Supervised Latent-Spaces PyTorch implementation and pretrained models for the paper. For details, see Watermarking Imag

Meta Research 32 Dec 13, 2022
MT-GAN-PyTorch - PyTorch Implementation of Learning to Transfer: Unsupervised Domain Translation via Meta-Learning

MT-GAN-PyTorch PyTorch Implementation of AAAI-2020 Paper "Learning to Transfer: Unsupervised Domain Translation via Meta-Learning" Dependency: Python

29 Oct 19, 2022
Gradient Step Denoiser for convergent Plug-and-Play

Source code for the paper "Gradient Step Denoiser for convergent Plug-and-Play"

Samuel Hurault 11 Sep 17, 2022
Codes for "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation"

CSDI This is the github repository for the NeurIPS 2021 paper "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation

106 Jan 04, 2023
Taichi Course Homework Template

太极图形课S1-标题部分 这个作业未来或将是你的开源项目，标题的内容可以来自作业中的核心关键词，让读者一眼看出你所完成的工作/做出的好玩demo 如果暂时未想好，起名时可以参考“太极图形课S1-xxx作业” 如下是作业（项目）展开说明的方法，可以帮大家理清思路，并且也对读者非常友好，请小伙伴们多多参

TaichiCourse 30 Nov 19, 2022
Adversarial Robustness Comparison of Vision Transformer and MLP-Mixer to CNNs

Adversarial Robustness Comparison of Vision Transformer and MLP-Mixer to CNNs ArXiv Abstract Convolutional Neural Networks (CNNs) have become the de f

Philipp Benz 12 Oct 24, 2022
PyTorch implementation of Pointnet2/Pointnet++

Pointnet2/Pointnet++ PyTorch Project Status: Unmaintained. Due to finite time, I have no plans to update this code and I will not be responding to iss

Erik Wijmans 1.2k Dec 29, 2022
QT Py Media Knob using rotary encoder & neopixel ring

QTPy-Knob QT Py USB Media Knob using rotary encoder & neopixel ring The QTPy-Knob features: Media knob for volume up/down/mute with "qtpy-knob.py" Cir

Tod E. Kurt 56 Dec 30, 2022
Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling

Permutation Invariant Graph Generation via Score-Based Generative Modeling This repo contains the official implementation for the paper Permutation In

64 Dec 29, 2022
PyTorch code for our paper "Attention in Attention Network for Image Super-Resolution"

Under construction... Attention in Attention Network for Image Super-Resolution (A2N) This repository is an PyTorch implementation of the paper "Atten

Haoyu Chen 71 Dec 30, 2022
[ACM MM2021] MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification

Introduction This project is developed based on FastReID, which is an ongoing ReID project. Projects BUC In projects/BUC, we implement AAAI 2019 paper

WuYiming 7 Apr 13, 2022
Full Resolution Residual Networks for Semantic Image Segmentation

Full-Resolution Residual Networks (FRRN) This repository contains code to train and qualitatively evaluate Full-Resolution Residual Networks (FRRNs) a

Toby Pohlen 274 Oct 27, 2022
Repositorio de los Laboratorios de Análisis Numérico / Análisis Numérico I de FAMAF, UNC.

Repositorio de los Laboratorios de Análisis Numérico / Análisis Numérico I de FAMAF, UNC. Para los Laboratorios de la materia, vamos a utilizar el len

Luis Biedma 18 Dec 12, 2022
Code accompanying the paper on "An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers" published at NeurIPS, 2021

Code for "An Empirical Investigation of Domian Generalization with Empirical Risk Minimizers" (NeurIPS 2021) Motivation and Introduction Domain Genera

Meta Research 15 Dec 27, 2022
Pytorch Implementation of PointNet and PointNet++++

Pytorch Implementation of PointNet and PointNet++ This repo is implementation for PointNet and PointNet++ in pytorch. Update 2021/03/27: (1) Release p

Luigi Ariano 1 Nov 11, 2021
Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs

Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs This is an implemetation of the paper Few-shot Relation Extraction via Baye

MilaGraph 36 Nov 22, 2022
unet for image segmentation

Implementation of deep learning framework -- Unet, using Keras The architecture was inspired by U-Net: Convolutional Networks for Biomedical Image Seg

zhixuhao 4.1k Dec 31, 2022