Python Quantum-machine-learning Resources

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

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

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

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

Overview This repository implements some common path planning algorithms used in robotics, including Search-based algorithms and Sampling-based algori

Tensorflow Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot of practice and contributi

The best way to use this material is by forking it by click the Fork button at the top, right corner. Then you will get your own copy to play with! Th

Conversational AI ChatBot Intelligent ChatBot built with Microsoft's DialoGPT transformer to make conversations with human users! In this project? Thi

Flight_fare-Prediction It is a Flight_fare Prediction Web Application Using Machine learning,Python and flask Using Machine leaning i have created a F

Seeing All the Angles: Learning Multiview Manipulation Policies for Contact-Rich Tasks from Demonstrations Trevor Ablett, Daniel (Yifan) Zhai, Jonatha

Book Recommendation System A recommendation system for suggesting new books given similar books. Datasets Dataset Kaggle Dataset Notebooks goodreads-E

Author Ibrahim Koné From-Machine-Learning-Models-To-WebAPI A collection of Machine Learning Models To Web Api which are built on open source technolog

Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities. This is aimed at those looking to get into the field of Data Science or those who are already in the field and looking to solve a real-world project with python.

Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.

Price-Prediction-For-a-Dream-Home ROADMAP TO THIS LINEAR REGRESSION BASED HOUSE PRICE PREDICTION PREDICTION MODEL Import all the dependencies of the p

Omdena-abuja-anpd - Automatic Number Plate Detection for the security of lives and properties using Computer Vision.

Stock Price Prediction Using Deep Learning Univariate Time Series Predicting stock price using historical data of a company using Neural networks for

Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities

Image-popularity-score - A novel deep regression method for image scoring.

Medical-Insurance-Cost-Prediction-using-Machine-learning - Here in this project, I will use regression analysis to predict medical insurance cost for people in different regions, and based on several aspects like : Smoking, Number of children, BMI...etc.

📚 Descrição Neste curso da Dell aprofundamos nossos conhecimentos em Machine Learning. 🖥️ Aulas (Em curso) 1.1 - Python aplicado a Data Science 1.2

House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin

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

BreastCancerDetection - This program is designed to predict two severity of abnormalities associated with breast cancer cells: benign and malignant. Mammograms from MIAS is preprocessed and features are extracted using the pre-trained CNN.

Scale complex AI/ML pipelines anywhere CodeFlare is a framework to simplify the integration, scaling and acceleration of complex multi-step analytics

CS5242_2021 Neural Networks and Deep Learning, NUS CS5242, 2021 Cloud Machine #1 : Google Colab (Free GPU) Follow this Notebook installation : https:/

VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion (Interspeech

House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin

Multi Task Learning for 3D segmentation Perception stack of an Autonomous Drivin

Apriori Apriori is an algorithm for frequent item set mining and association rul

Kata: Clean Machine Learning From Dirty Code First, open the Kata in Google Colab (or else download it) You can clone this project and launch jupyter-

Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L

A Survey on Deep Learning Technique for Video Segmentation A Survey on Deep Learning Technique for Video Segmentation Wenguan Wang, Tianfei Zhou, Fati