2210 Repositories
Python turing-machine-simulator Libraries
Aws-machine-learning-university-accelerated-tab - Machine Learning University: Accelerated Tabular Data Class
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, published by Packt
Hands-On Machine Learning for Algorithmic Trading Hands-On Machine Learning for Algorithmic Trading, published by Packt This is the code repository fo
Prml - Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop
Pattern Recognition and Machine Learning (PRML) This project contains Jupyter notebooks of many the algorithms presented in Christopher Bishop's Patte
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models
Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor
ML course - EPFL Machine Learning Course, Fall 2021
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
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow
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 - Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).
Saliency Methods 🔴 Now framework-agnostic! (Example core notebook) 🔴 🔗 For further explanation of the methods and more examples of the resulting ma
Kaggle-titanic - A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.
Kaggle-titanic This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this reposito
Video2x - A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR.
Official Discussion Group (Telegram): https://t.me/video2x A Discord server is also available. Please note that most developers are only on Telegram.
Client - 🔥 A tool for visualizing and tracking your machine learning experiments
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
A supercharged version of paperless: scan, index and archive all your physical documents
Paperless-ng Paperless (click me) is an application by Daniel Quinn and contributors that indexes your scanned documents and allows you to easily sear
Conversational-AI-ChatBot - Intelligent ChatBot built with Microsoft's DialoGPT transformer to make conversations with human users!
Conversational AI ChatBot Intelligent ChatBot built with Microsoft's DialoGPT transformer to make conversations with human users! In this project? Thi
Flightfare-Prediction - It is a Flightfare Prediction Web Application Using Machine learning,Python and flask
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
A recommendation system for suggesting new books given similar books.
Book Recommendation System A recommendation system for suggesting new books given similar books. Datasets Dataset Kaggle Dataset Notebooks goodreads-E
A collection of Machine Learning Models To Web Api which are built on open source technologies/frameworks like Django, Flask.
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
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.
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 - A machine learning based linear regression trained model for house price prediction.
Price-Prediction-For-a-Dream-Home ROADMAP TO THIS LINEAR REGRESSION BASED HOUSE PRICE PREDICTION PREDICTION MODEL Import all the dependencies of the p
Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities
Mortgage-loan-prediction - Show how to perform advanced Analytics and Machine Learning in Python using a full complement of PyData utilities
Medical Insurance Cost Prediction using Machine earning
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.
Machine-learning-dell - Repositório com as atividades desenvolvidas no curso de Machine Learning
📚 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_kaggle - Predict sales prices and practice feature engineering, RFs, and gradient boosting
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.
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
Codeflare - Scale complex AI/ML pipelines anywhere
Scale complex AI/ML pipelines anywhere CodeFlare is a framework to simplify the integration, scaling and acceleration of complex multi-step analytics
Houseprices - Predict sales prices and practice feature engineering, RFs, and gradient boosting
House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin
Clean Machine Learning, a Coding Kata
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-
Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku
Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L
Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible
IMBENS: Class-imbalanced Ensemble Learning in Python Language: English | Chinese/中文 Links: Documentation | Gallery | PyPI | Changelog | Source | Downl
The codebase for Data-driven general-purpose voice activity detection.
Data driven GPVAD Repository for the work in TASLP 2021 Voice activity detection in the wild: A data-driven approach using teacher-student training. S
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode
Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019
USSS_ICCV19 Code for Universal Semi Supervised Semantic Segmentation accepted to ICCV 2019. Full Paper available at https://arxiv.org/abs/1811.10323.
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
Deep SAD: A Method for Deep Semi-Supervised Anomaly Detection This repository provides a PyTorch implementation of the Deep SAD method presented in ou
MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification
MixText This repo contains codes for the following paper: Jiaao Chen, Zichao Yang, Diyi Yang: MixText: Linguistically-Informed Interpolation of Hidden
Beibo is a Python library that uses several AI prediction models to predict stocks returns over a defined period of time.
Beibo is a Python library that uses several AI prediction models to predict stocks returns over a defined period of time.
PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE).
GRACE The official PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE). For a thorough resource collection of self-superv
Deep Hedging Demo - An Example of Using Machine Learning for Derivative Pricing.
Deep Hedging Demo Pricing Derivatives using Machine Learning 1) Jupyter version: Run ./colab/deep_hedging_colab.ipynb on Colab. 2) Gui version: Run py
In this work, we will implement some basic but important algorithm of machine learning step by step.
WoRkS continued English 中文 Français Probability Density Estimation-Non-Parametric Methods(概率密度估计-非参数方法) 1. Kernel / k-Nearest Neighborhood Density Est
Numerical Methods with Python, Numpy and Matplotlib
Numerical Bric-a-Brac Collections of numerical techniques with Python and standard computational packages (Numpy, SciPy, Numba, Matplotlib ...). Diffe
PyCharge is an open-source computational electrodynamics Python simulator
PyCharge PyCharge is an open-source computational electrodynamics Python simulator that can calculate the electromagnetic fields and potentials genera
Python library for parsing resumes using natural language processing and machine learning
CVParser Python library for parsing resumes using natural language processing and machine learning. Setup Installation on Linux and Mac OS Follow the
A webpage that utilizes machine learning to extract sentiments from tweets.
Tweets_Classification_Webpage The goal of this project is to be able to predict what rating customers on social media platforms would give to products
Python scripts aim to use a Random Forest machine learning algorithm to predict the water affinity of Metal-Organic Frameworks
The following Python scripts aim to use a Random Forest machine learning algorithm to predict the water affinity of Metal-Organic Frameworks (MOFs). The training set is extracted from the Cambridge Structural Database and the CoRE_MOF 2019 dataset.
The implementation of Parameter Differentiation based Multilingual Neural Machine Translation .
The implementation of Parameter Differentiation based Multilingual Neural Machine Translation .
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe
Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa
The implementation of Parameter Differentiation based Multilingual Neural Machine Translation
The implementation of Parameter Differentiation based Multilingual Neural Machin
This is a Python program that implements a vacuum cleaner as an Artificial Intelligence.
Vacuum-Cleaner Python3 This is a Python3 agent that implements a simulator for a vacuum cleaner and it is introduction to Artificial Intelligence. A s
whylogs: A Data and Machine Learning Logging Standard
whylogs: A Data and Machine Learning Logging Standard whylogs is an open source standard for data and ML logging whylogs logging agent is the easiest
txtai: Build AI-powered semantic search applications in Go
txtai: Build AI-powered semantic search applications in Go txtai executes machine-learning workflows to transform data and build AI-powered semantic s
A deep learning model for style-specific music generation.
DeepJ: A model for style-specific music generation https://arxiv.org/abs/1801.00887 Abstract Recent advances in deep neural networks have enabled algo
Multilingual word vectors in 78 languages
Aligning the fastText vectors of 78 languages Facebook recently open-sourced word vectors in 89 languages. However these vectors are monolingual; mean
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
News December 27: v1.1.0 New loss functions: CentroidTripletLoss and VICRegLoss Mean reciprocal rank + per-class accuracies See the release notes Than
Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.
The Ultimate PyTorch Source-Build Template Translations: 한국어 TL;DR PyTorch built from source can be x4 faster than a naïve PyTorch install. This repos
Final project for machine learning (CSC 590). Detection of hepatitis C and progression through blood samples.
Hepatitis C Blood Based Detection Final project for machine learning (CSC 590). Dataset from Kaggle. Using data from previous hepatitis C blood panels
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
2021: A Year Full of Amazing AI papers- A Review 📌 A curated list of the latest breakthroughs in AI by release date with a clear video explanation, l
All-in-one web-based development environment for machine learning
All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu
Python Moonlight (Machine Learning) Practice
PyML Python Moonlight (Machine Learning) Practice Contents Design Documentation Prerequisites Checklist Dev Setup Testing Run Prerequisites Python 3 P
Implementation of Memory-Efficient Neural Networks with Multi-Level Generation, ICCV 2021
Memory-Efficient Multi-Level In-Situ Generation (MLG) By Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen and David Z. Pan
Machine Learning Course Project, IMDB movie review sentiment analysis by lstm, cnn, and transformer
IMDB Sentiment Analysis This is the final project of Machine Learning Courses in Huazhong University of Science and Technology, School of Artificial I
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size.
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size. The hub data layout enables rapid transformations and streaming of data while training models at scale. Hub is used by Google, Waymo, Red Cross, Oxford University, and Omdena.
How to Learn a Domain Adaptive Event Simulator? ACM MM, 2021
LETGAN How to Learn a Domain Adaptive Event Simulator? ACM MM 2021 Running Environment: pytorch=1.4, 1 NVIDIA-1080TI. More details can be found in pap
Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2021)
Applied Machine Learning (Cornell CS5785, Fall 2021) This repo contains executable course notes and slides for the Applied ML course at Cornell and Co
Example GUI for Command line capable machine learning programs
Example GUI for Command line capable machine learning programs This is an example GUI made in PysimpleGUI and Tkinter, mainly for machine learning pro
A repository to index and organize the latest machine learning courses found on YouTube.
📺 ML YouTube Courses At DAIR.AI we ❤️ open education. We are excited to share some of the best and most recent machine learning courses available on
A lightweight tool to get an AI Infrastructure Stack up in minutes not days.
K3ai will take care of setup K8s for You, deploy the AI tool of your choice and even run your code on it.
Deploy recommendation engines with Edge Computing
RecoEdge: Bringing Recommendations to the Edge A one stop solution to build your recommendation models, train them and, deploy them in a privacy prese
Tensor-Based Quantum Machine Learning
TensorLy_Quantum TensorLy-Quantum is a Python library for Tensor-Based Quantum Machine Learning that builds on top of TensorLy and PyTorch. Website: h
High accurate tool for automatic faces detection with landmarks
faces_detanator High accurate tool for automatic faces detection with landmarks. The library is based on public detectors with high accuracy (TinaFace
An automated program that helps customers of Pizza Palour place their pizza orders
PIzza_Order_Assistant Introduction An automated program that helps customers of Pizza Palour place their pizza orders. The program uses voice commands
BisQue is a web-based platform designed to provide researchers with organizational and quantitative analysis tools for 5D image data. Users can extend BisQue by implementing containerized ML workflows.
Overview BisQue is a web-based platform specifically designed to provide researchers with organizational and quantitative analysis tools for up to 5D
PyBERT is a serial communication link bit error rate tester simulator with a graphical user interface (GUI).
PyBERT PyBERT is a serial communication link bit error rate tester simulator with a graphical user interface (GUI). It uses the Traits/UI package of t
Uses machine learning to scan the similarity of two texts
PlagiarismChecker Uses machine learning to scan the similarity of two documents. End Points: http://localhost:3000/register (create a/c) http://localh
Neptune client library - integrate your Python scripts with Neptune
Lightweight experiment tracking tool for AI/ML individuals and teams. Fits any workflow. Neptune is a lightweight experiment logging/tracking tool tha
A Lightweight NLP Data Loader for All Deep Learning Frameworks in Python
LineFlow: Framework-Agnostic NLP Data Loader in Python LineFlow is a simple text dataset loader for NLP deep learning tasks. LineFlow was designed to
Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.
Welcome to Spokestack Python! This library is intended for developing voice interfaces in Python. This can include anything from Raspberry Pi applicat
LynxKite: a complete graph data science platform for very large graphs and other datasets.
LynxKite is a complete graph data science platform for very large graphs and other datasets. It seamlessly combines the benefits of a friendly graphical interface and a powerful Python API.
Neural network chess engine trained on Gary Kasparov's games.
Neural Chess It's not the best chess engine, but it is a chess engine. Proof of concept neural network chess engine (feed-forward multi-layer perceptr
Implemented four supervised learning Machine Learning algorithms
Implemented four supervised learning Machine Learning algorithms from an algorithmic family called Classification and Regression Trees (CARTs), details see README_Report.
The reference baseline of final exam for XMU machine learning course
Mini-NICO Baseline The baseline is a reference method for the final exam of machine learning course. Requirements Installation we use /python3.7 /torc
Source code of SIGIR2021 Paper 'One Chatbot Per Person: Creating Personalized Chatbots based on Implicit Profiles'
DHAP Source code of SIGIR2021 Long Paper: One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles . Preinstallation Fir
Weakly Supervised End-to-End Learning (NeurIPS 2021)
WeaSEL: Weakly Supervised End-to-end Learning This is a PyTorch-Lightning-based framework, based on our End-to-End Weak Supervision paper (NeurIPS 202
A visualization tool to show a TensorFlow's graph like TensorBoard
tfgraphviz tfgraphviz is a module to visualize a TensorFlow's data flow graph like TensorBoard using Graphviz. tfgraphviz enables to provide a visuali
This library is a location of the LegacyLogger for PyTorch Lightning.
neptune-contrib Documentation See neptune-contrib documentation site Installation Get prerequisites python versions 3.5.6/3.6 are supported Install li
keep your machine's shell history synchronize
SyncShell Yet another tool for laziness Keep your machine's shell history synchronize Get SyncShell Currently, SyncShell is just available on PyPi and
💀mummify: a version control tool for machine learning
mummify is a version control tool for machine learning. It's simple, fast, and designed for model prototyping.
An End-to-End Machine Learning Library to Optimize AUC (AUROC, AUPRC).
Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a
PyTea: PyTorch Tensor shape error analyzer
PyTea: PyTorch Tensor Shape Error Analyzer paper project page Requirements node.js = 12.x python = 3.8 z3-solver = 4.8 How to install and use # ins
Coronavirus whatsapp chatbot to give real time info on covid
Covy Developed a coronavirus whatsapp chatbot which gives case counts in a particular district, city, state or country. It also predicts future cases
All the code and files related to the MI-Lab of UE19CS305 course in sem 5
Machine-Intelligence-Lab-CS305 The compilation of all the code an drelated files from MI-Lab UE19CS305 (of batch 2019-2023) offered by PES University
Code for the paper: Adversarial Machine Learning: Bayesian Perspectives
Code for the paper: Adversarial Machine Learning: Bayesian Perspectives This repository contains code for reproducing the experiments in the ** Advers
SIR model parameter estimation using a novel algorithm for differentiated uniformization.
TenSIR Parameter estimation on epidemic data under the SIR model using a novel algorithm for differentiated uniformization of Markov transition rate m
Latte: Cross-framework Python Package for Evaluation of Latent-based Generative Models
Cross-framework Python Package for Evaluation of Latent-based Generative Models Latte Latte (for LATent Tensor Evaluation) is a cross-framework Python
Hotpile: High Order Turing Machine Language Compiler
Hotpile: High Order Turing Machine Language Compiler Build and Run Requirements: Python 3.6+, bison, flex, and GCC installed. Needs to be run under UN
Open source annotation tool for machine learning practitioners.
doccano doccano is an open source text annotation tool for humans. It provides annotation features for text classification, sequence labeling and sequ
Python / C++ based particle reaction-diffusion simulator
ReaDDy (Reaction Diffusion Dynamics) is an open source particle based reaction-diffusion simulator that can be configured and run via Python. Currentl
Python PID Controller and Process Simulator (FOPDT) with GUI.
PythonPID_Simulator Python PID Controller and Process Simulator (FOPDT) with GUI. Run the File. Then select Model Values and Tune PID.. Hit Refresh to
TypeRig is a Python library aimed at simplifying the current FontLab API
TypeRig TypeRig is a Python library aimed at simplifying the current FontLab API while offering some additional functionality that is heavily biased t