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
Vanilla and Prototypical Networks with Random Weights for image classification on Omniglot and mini-ImageNet. Made with Python3.

vanilla-rw-protonets-project Vanilla Prototypical Networks and PNs with Random Weights for image classification on Omniglot and mini-ImageNet. Made wi

Giovani Candido 8 Aug 31, 2022
Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?

Adversrial Machine Learning Benchmarks This code belongs to the papers: Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness? Det

Adversarial Machine Learning 9 Nov 27, 2022
Dictionary Learning with Uniform Sparse Representations for Anomaly Detection

Dictionary Learning with Uniform Sparse Representations for Anomaly Detection Implementation of the Uniform DL Representation for AD algorithm describ

Paul Irofti 1 Nov 23, 2022
Training PSPNet in Tensorflow. Reproduce the performance from the paper.

Training Reproduce of PSPNet. (Updated 2021/04/09. Authors of PSPNet have provided a Pytorch implementation for PSPNet and their new work with support

Li Xuhong 126 Jul 13, 2022
LogAvgExp - Pytorch Implementation of LogAvgExp

LogAvgExp - Pytorch Implementation of LogAvgExp for Pytorch Install $ pip instal

Phil Wang 31 Oct 14, 2022
Computer Vision application in the web

Computer Vision application in the web Preview Usage Clone this repo git clone https://github.com/amineHY/WebApp-Computer-Vision-streamlit.git cd Web

Amine Hadj-Youcef. PhD 35 Dec 06, 2022
Comp445 project - Data Communications & Computer Networks

COMP-445 Data Communications & Computer Networks Change Python version in Conda

Peng Zhao 2 Oct 03, 2022
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce (EMNLP Founding 2021)

Introduction K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce. Installation PyTor

Xu Song 21 Nov 16, 2022
This code is an implementation for Singing TTS.

MLP Singer This code is an implementation for Singing TTS. The algorithm is based on the following papers: Tae, J., Kim, H., & Lee, Y. (2021). MLP Sin

Heejo You 22 Dec 23, 2022
CS_Final_Metal_surface_detection - This is a final project for CoderSchool Machine Learning bootcamp on 29/12/2021.

CS_Final_Metal_surface_detection This is a final project for CoderSchool Machine Learning bootcamp on 29/12/2021. The project is based on the dataset

Cuong Vo 1 Dec 29, 2021
PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).

Scaffold-Federated-Learning PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020). Environment numpy=

KI 30 Dec 29, 2022
PAthological QUpath Obsession - QuPath and Python conversations

PAQUO: PAthological QUpath Obsession Welcome to paquo 👋 , a library for interacting with QuPath from Python. paquo's goal is to provide a pythonic in

Bayer AG 60 Dec 31, 2022
Solving reinforcement learning tasks which require language and vision

Multimodal Reinforcement Learning JAX implementations of the following multimodal reinforcement learning approaches. Dual-coding Episodic Memory from

Henry Prior 31 Feb 26, 2022
A cross-document event and entity coreference resolution system, trained and evaluated on the ECB+ corpus.

A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference Resolution. Introduction This repo contains experimental code derived from

2 May 09, 2022
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

timeseriesAI 2.8k Jan 08, 2023
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

DLR-RM 4.7k Jan 01, 2023
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

TL;DR Ignite is a high-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Click on the image to

4.2k Jan 01, 2023
Testability-Aware Low Power Controller Design with Evolutionary Learning, ITC2021

Testability-Aware Low Power Controller Design with Evolutionary Learning This repo contains the source code of Testability-Aware Low Power Controller

Lee Man 1 Dec 26, 2021
This repository is for DSA and CP scripts for reference.

dsa-script-collections This Repo is the collection of DSA and CP scripts for reference. Contents Python Bubble Sort Insertion Sort Merge Sort Quick So

Aditya Kumar Pandey 9 Nov 22, 2022
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning

SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning This repository is the official implementation of "SHRIMP: Sparser Random Featur

Bobby Shi 0 Dec 16, 2021