Python Automated-machine-learning Resources

The GatedTabTransformer. A deep learning tabular classification architecture inspired by TabTransformer with integrated gated multilayer perceptron. C

Replication Code for 'Moving On' - Investigating Inventors' Ethnic Origins Using Supervised Learning This repository contains the code to replicate th

FaceQgen FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment This repository is based on the paper: "FaceQgen: Semi-Supervised D

Machine learning approaches for localized lockdown, subnotification analysis and cases forecasting in São Paulo state counties during COVID-19 pandemi

Mammoth - An Extendible (General) Continual Learning Framework for Pytorch NEWS STAY TUNED: We are working on an update of this repository to include

Supplementary Materials for CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels This repository includes all supplementary mater

Deep Transfer Learning on PyTorch This is a PyTorch library for deep transfer learning. We divide the code into two aspects: Single-source Unsupervise

Image Segmentation with U-Net Algorithm on Carvana Dataset using AWS Sagemaker This is a full project of image segmentation using the model built with

libsdae - deep-Autoencoder & denoising autoencoder A simple Tensorflow based library for Deep autoencoder and denoising AE. Library follows sklearn st

VolumeGAN - 3D-aware Image Synthesis via Learning Structural and Textural Representations 3D-aware Image Synthesis via Learning Structural and Textura

Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll

TuiGAN-PyTorch Official PyTorch Implementation of "TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images" (ECCV 2020 Spotligh

Neural Wireframe Renderer: Learning Wireframe to Image Translations Pytorch implementation of ideas from the paper Neural Wireframe Renderer: Learning

Tensorflow implementation for CVPR2020 paper “Learning to Cartoonize Using White-box Cartoon Representations”.

CoCosNet Pytorch Implementation of the paper "Cross-domain Correspondence Learning for Exemplar-based Image Translation" (CVPR 2020 oral). Update: 202

STEFANN: Scene Text Editor using Font Adaptive Neural Network @ The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020.

NICE-GAN-pytorch - Official PyTorch implementation of NICE-GAN: Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation

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

GANILLA We provide PyTorch implementation for: GANILLA: Generative Adversarial Networks for Image to Illustration Translation. Paper Arxiv Updates (Fe

Future urban scene generation through vehicle synthesis This repository contains Pytorch code for the ICPR2020 paper "Future Urban Scene Generation Th

人像卡通化 (Photo to Cartoon) 中文版 | English Version 该项目为小视科技卡通肖像探索项目。您可使用微信扫描下方二维码或搜索“AI卡通秀”小程序体验卡通化效果。

Multi-Domain Multi-Modality I2I translation Pytorch implementation of multi-modality I2I translation for multi-domains. The project is an extension to

RL-GAN: Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation RL-GAN is an official implementation of the paper: T

AttentionGAN-v2 for Unpaired Image-to-Image Translation AttentionGAN-v2 Framework The proposed generator learns both foreground and background attenti

Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle

ICCV paper of DualGAN DualGAN: unsupervised dual learning for image-to-image translation please cite the paper, if the codes has been used for your re

Scan2Cap: Context-aware Dense Captioning in RGB-D Scans Introduction We introduce the task of dense captioning in 3D scans from commodity RGB-D sensor

Learning to Generate Grounded Visual Captions without Localization Supervision This is the PyTorch implementation of our paper: Learning to Generate G

Object Relation Transformer This is a PyTorch implementation of the Object Relation Transformer published in NeurIPS 2019. You can find the paper here

Awesome-Visual-Captioning Table of Contents ACL-2021 CVPR-2021 AAAI-2021 ACMMM-2020 NeurIPS-2020 ECCV-2020 CVPR-2020 ACL-2020 AAAI-2020 ACL-2019 NeurI

Fashion-Entity-Classification - Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. Zalando intends Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.

Skill-vs-chance-games-analysis - Finding a method to objectively quantify skill versus chance in games, using reinforcement learning

CANDIY-spectrum Human analyis of chemical spectra such as Mass Spectra (MS), Inf

Machine care An simple python script to take care of simple maintenance tasks fo

dependencies for project: cmake 3.22.1 dlib 19.22.1 face-recognition 1.3.0 openc

Adversarial Autoencoders (AAE) Tensorflow implementation of Adversarial Autoencoders (ICLR 2016) Similar to variational autoencoder (VAE), AAE imposes

Deep Reinforcement Learning in TensorFlow TensorFlow implementation of Deep Reinforcement Learning papers. This implementation contains: [1] Playing A

ddpg-aigym Deep Deterministic Policy Gradient Implementation of Deep Deterministic Policy Gradiet Algorithm (Lillicrap et al.arXiv:1509.02971.) in Ten

DeepRL This code implements the standard deep Q-learning and dueling network with experience replay (memory buffer) for playing simple games. DQN algo

Deep Residual Learning for Image Recognition This is a Torch implementation of "Deep Residual Learning for Image Recognition",Kaiming He, Xiangyu Zhan

Deep Learning - Image Captioning with Convolutional and Recurrent Neural Nets ========================================================================

Seq2seq Sequence to Sequence Learning with Keras Hi! You have just found Seq2Seq. Seq2Seq is a sequence to sequence learning add-on for the python dee

Neural Machine Translation (seq2seq) Tutorial Authors: Thang Luong, Eugene Brevdo, Rui Zhao (Google Research Blogpost, Github) This version of the tut

fidelipy fidelipy is a simple Python 3.7+ library for semi-automated trading on fidelity.com. The scope is limited to the Trade Stocks/ETFs simplified

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio

COVID Predictions This repo contains ML models to be trained on COVID-19 data from the UK, sourced off of Kaggle here. This uses many different ML mod

ML-PersonalWork - Big assignment PersonalWork in Machine Learning, 2021 autumn BUAA.

0. Introduction This repository contains the source code for our SIGCOMM'21 paper "Network Planning with Deep Reinforcement Learning". Notes The netwo

LightningFSL: Few-Shot Learning with Pytorch-Lightning In this repo, a number of pytorch-lightning implementations of FSL algorithms are provided, inc

Documentation pythae This library implements some of the most common (Variational) Autoencoder models. In particular it provides the possibility to pe

Scene-Change-Detection - A video scene detection algorithm is designed to detect a variety of different scenes within a video. There is a very simple definition for a scene: It is a series of logically and chronologically related shots taken in a specific order to depict an over-arching concept or story.

LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating (Dataset) The dataset is from Amazon Review Data (2018)

Machine Learning Research 1. Project Topic 1.1. Exsiting research Benmark: https://paperswithcode.com/sota ACL anthology for NLP papers: http://www.ac

stroke-predictions-ml-model machine learning model to predict individuals chance

CorrProxies - Optimizing Machine Learning Inference Queries with Correlative Proxy Models

Enigma-Plus Python based Enigma machine simulator with some extra features Examp

Pytest python example with automated testing This is a minimal viable example of pytest with an automated run of tests for every push/merge into the m

Whatsapp Automated Wishes Helps to send automated wishes to your contacts in Whatsapp at scheduled time using pywhatkit . Written for Raspberry pi. Wi

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

BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation function along with stochastic gradient descent to adjust the weights and biases.

Unofficial Google Colaboratory Notebook and Repository Gallery Please contact me to take over and revamp this repo (it gets around 30k views and 200k

Deep-Learning-Book-Chapter-Summaries This repository provides a summary for each chapter of the Deep Learning book by Ian Goodfellow, Yoshua Bengio an

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

This is not an official Google product ml-design-patterns Source code accompanying O'Reilly book: Title: Machine Learning Design Patterns Authors: Val

data-science-on-gcp Source code accompanying book: Data Science on the Google Cloud Platform, 2nd Edition Valliappa Lakshmanan O'Reilly, Jan 2022 Bran

Awesome AI books Some awesome AI related books and pdfs for downloading and learning. Preface This repo only used for learning, do not use in business

Self-Learning This repository is intended to be used for personal use, all rights reserved to respective owners, please cite original authors and ask

Non-tech crash course into Operação Serenata de Amor Tech crash course into Operação Serenata de Amor Contributing with code and tech skills Supportin

A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers

Deep Learning - All You Need to Know Sponsorship To support maintaining and upgrading this project, please kindly consider Sponsoring the project deve

Tianshou (天授) is a reinforcement learning platform based on pure PyTorch. Unlike existing reinforcement learning libraries, which are mainly based on

the people's comma the paper Learning a Driving Simulator the comma.ai driving dataset 7 and a quarter hours of largely highway driving. Enough to tra

AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

GANs in Action by Jakub Langr and Vladimir Bok List of available code: Chapter 2: Colab, Notebook Chapter 3: Notebook Chapter 4: Notebook Chapter 6: C

Partial Convolutions for Image Inpainting using Keras Keras implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions", https

Coursera Machine Learning This repository contains python implementations of certain exercises from the course by Andrew Ng. For a number of assignmen

TensorFlow-LiveLessons Note that the second edition of this video series is now available here. The second edition contains all of the content from th

Coursera Assignments This repository is aimed to help Coursera learners who have difficulties in their learning process. The quiz and programming home

Mã nguồn cuốn ebook "Machine Learning cơ bản", Vũ Hữu Tiệp. ebook Machine Learning cơ bản pdf-black_white, pdf-color. Mọi hình thức sao chép, in ấn đề

📑 Introduction A curated collection of Amazing Python scripts from Basics to Advance with automation task scripts. This is your Personal space to fin

Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Speech Emotion Analyzer The idea behind creating this project was to build a machine learning model that could detect emotions from the speech we have

Machine Learning University: Accelerated Tabular Data Class This repository contains slides, notebooks, and datasets for the Machine Learning Universi

Hands-On Machine Learning for Algorithmic Trading Hands-On Machine Learning for Algorithmic Trading, published by Packt This is the code repository fo

Pattern Recognition and Machine Learning (PRML) This project contains Jupyter notebooks of many the algorithms presented in Christopher Bishop's Patte

Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor

EPFL Machine Learning Course CS-433 Machine Learning Course, Fall 2021 Repository for all lecture notes, labs and projects - resources, code templates

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

This repository has become incompatible with the latest and recommended version of Tensorflow 2.0 Instead of refactoring this code painfully, I create

Finetune AlexNet with Tensorflow Update 15.06.2016 I revised the entire code base to work with the new input pipeline coming with TensorFlow = versio

TensorFlow 101: Introduction to Deep Learning I have worked all my life in Machine Learning, and I've never seen one algorithm knock over its benchmar

Saliency Methods 🔴 Now framework-agnostic! (Example core notebook) 🔴 🔗 For further explanation of the methods and more examples of the resulting ma

Kaggle-titanic This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this reposito

As much as this series is to educate aspiring computer programmers and data scientists of all ages and all backgrounds, it is also a reminder to mysel

Introduction to Deep Learning course resources https://www.coursera.org/learn/intro-to-deep-learning Running on Google Colab (tested for all weeks) Go

Official Discussion Group (Telegram): https://t.me/video2x A Discord server is also available. Please note that most developers are only on Telegram.

Weights and Biases Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to produ

Paperless-ng Paperless (click me) is an application by Daniel Quinn and contributors that indexes your scanned documents and allows you to easily sear

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Created by Charles R. Qi, Hao Su, Kaichun Mo, Leonidas J. Guibas from Sta