2221 Repositories
Python gradient-boosting-machine Libraries
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
NCVX NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning. Please check https://ncvx.org for detailed instruction
A benchmark dataset for emulating atmospheric radiative transfer in weather and climate models with machine learning (NeurIPS 2021 Datasets and Benchmarks Track)
ClimART - A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models Official PyTorch Implementation Using deep le
A simple rest api serving a deep learning model that classifies human gender based on their faces. (vgg16 transfare learning)
this is a simple rest api serving a deep learning model that classifies human gender based on their faces. (vgg16 transfare learning)
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery
PyTorch implementation for the Neuro-Symbolic Sudoku Solver leveraging the power of Neural Logic Machines (NLM)
Neuro-Symbolic Sudoku Solver PyTorch implementation for the Neuro-Symbolic Sudoku Solver leveraging the power of Neural Logic Machines (NLM). Please n
DuBE: Duple-balanced Ensemble Learning from Skewed Data
DuBE: Duple-balanced Ensemble Learning from Skewed Data "Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning" (IEEE ICDE 2022 S
IMBENS: class-imbalanced ensemble learning in Python.
IMBENS: class-imbalanced ensemble learning in Python. Links: [Documentation] [Gallery] [PyPI] [Changelog] [Source] [Download] [知乎/Zhihu] [ä¸æ–‡README] [a
Research code for the paper "Variational Gibbs inference for statistical estimation from incomplete data".
Variational Gibbs inference (VGI) This repository contains the research code for Simkus, V., Rhodes, B., Gutmann, M. U., 2021. Variational Gibbs infer
Simple command line tool to train and deploy your machine learning models with AWS SageMaker
metamaker Simple command line tool to train and deploy your machine learning models with AWS SageMaker Features metamaker enables you to: Build a dock
This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models.
FFG-benchmarks This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models. What is Fe
Large scale and asynchronous Hyperparameter Optimization at your fingertip.
Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option
A basic tool to generate Hydrogen drum machine kits.
Generate Hydrogen Kit A basic tool to generate drumkit.xml files for Hydrogen drum machine. Saves a bit of time when making kits. Supply it with a nam
A Machine Teaching Framework for Scalable Recognition
MEMORABLE This repository contains the source code accompanying our ICCV 2021 paper. A Machine Teaching Framework for Scalable Recognition Pei Wang, N
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
PointCNN: Convolution On X-Transformed Points Created by Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen. Introduction PointCNN
Training open neural machine translation models
Train Opus-MT models This package includes scripts for training NMT models using MarianNMT and OPUS data for OPUS-MT. More details are given in the Ma
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
Haystack is an open source NLP framework that leverages Transformer models.
Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want
Simple and Distributed Machine Learning
Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy
Qlib is an AI-oriented quantitative investment platform
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment.
Pytorch implementation of NeurIPS 2021 paper: Geometry Processing with Neural Fields.
Geometry Processing with Neural Fields Pytorch implementation for the NeurIPS 2021 paper: Geometry Processing with Neural Fields Guandao Yang, Serge B
High performance distributed framework for training deep learning recommendation models based on PyTorch.
PERSIA (Parallel rEcommendation tRaining System with hybrId Acceleration) is developed by AI platform@Kuaishou Technology, collaborating with ETH. It
Conversational text Analysis using various NLP techniques
PyConverse Let me try first Installation pip install pyconverse Usage Please try this notebook that demos the core functionalities: basic usage noteb
Forecasting prices using Facebook/Meta's Prophet model
CryptoForecasting using Machine and Deep learning (Part 1) CryptoForecasting using Machine Learning The main aspect of predicting the stock-related da
Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.
Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.
Learning Convolutional Neural Networks with Interactive Visualization.
CNN Explainer An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs) For more information,
LLVM-based compiler for LightGBM gradient-boosted trees. Speeds up prediction by ≥10x.
LLVM-based compiler for LightGBM gradient-boosted trees. Speeds up prediction by ≥10x.
Reinforcement learning library in JAX.
Reinforcement learning library in JAX.
A collection of online resources to help you on your Tech journey.
Everything Tech Resources & Projects About The Project Coming from an engineering background and looking to up skill yourself on a new field can be di
Scikit-Learn useful pre-defined Pipelines Hub
Scikit-Pipes Scikit-Learn useful pre-defined Pipelines Hub Usage: Install scikit-pipes It's advised to install sklearn-genetic using a virtual env, in
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".
Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without
Official Repo of my work for SREC Nandyal Machine Learning Bootcamp
About the Bootcamp A 3-day Machine Learning Bootcamp organised by Department of Electronics and Communication Engineering, Santhiram Engineering Colle
CD) in machine learning projectsImplementing continuous integration & delivery (CI/CD) in machine learning projects
CML with cloud compute This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Cookiecutter Data Science A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. Project homepage
PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)
PandaPy "I came across PandaPy last week and have already used it in my current project. It is a fascinating Python library with a lot of potential to
Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and many other libraries. Documenta
BudouX is the successor to Budou, the machine learning powered line break organizer tool.
BudouX Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning powered line break organizer tool. It is standalone
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
Softlearning Softlearning is a deep reinforcement learning toolbox for training maximum entropy policies in continuous domains. The implementation is
Keyword spotting on Arm Cortex-M Microcontrollers
Keyword spotting for Microcontrollers This repository consists of the tensorflow models and training scripts used in the paper: Hello Edge: Keyword sp
Source code for CVPR 2020 paper "Learning to Forget for Meta-Learning"
L2F - Learning to Forget for Meta-Learning Sungyong Baik, Seokil Hong, Kyoung Mu Lee Source code for CVPR 2020 paper "Learning to Forget for Meta-Lear
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.
BOF-Roaster is an automated buffer overflow exploit machine which is begin written with Python 3.
BOF-Roaster is an automated buffer overflow exploit machine which is begin written with Python 3. On first release it was able to successfully break many of the most well-known buffer overflow example executables.
Machine Learning Framework for Operating Systems - Brings ML to Linux kernel
KML: A Machine Learning Framework for Operating Systems & Storage Systems Storage systems and their OS components are designed to accommodate a wide v
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard We
This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression problems
Doctoral dissertation of Zheng Zhao This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression pro
Reproduced Code for Image Forgery Detection papers.
Image Forgery Detection With over 4.5 billion active internet users, the amount of multimedia content being shared every day has surpassed everyone’s
🧪 Cutting-edge experimental spaCy components and features
spacy-experimental: Cutting-edge experimental spaCy components and features This package includes experimental components and features for spaCy v3.x,
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)
MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes
The fastai book, published as Jupyter Notebooks
English / Spanish / Korean / Chinese / Bengali / Indonesian The fastai book These notebooks cover an introduction to deep learning, fastai, and PyTorc
Walk with fastai
Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Walk with fastai What is this p
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
A modular domain adaptation library written in PyTorch.
A modular domain adaptation library written in PyTorch.
The Most Efficient Temporal Difference Learning Framework for 2048
moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar
MLJetReconstruction - using machine learning to reconstruct jets for CMS
MLJetReconstruction - using machine learning to reconstruct jets for CMS The C++ data extraction code used here was based heavily on that foundv here.
cleanlab is the data-centric ML ops package for machine learning with noisy labels.
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis.
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.
Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas.
Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas. Its objective is to ex
dirty_cat is a Python module for machine-learning on dirty categorical variables.
dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models.
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow scikit-learn's functionality with fit() and transform() methods to first learn the transforming parameters from data and then transform the data.
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Feature Engineering & Feature Selection A comprehensive guide [pdf] [markdown] for Feature Engineering and Feature Selection, with implementations and
stability-selection - A scikit-learn compatible implementation of stability selection
stability-selection - A scikit-learn compatible implementation of stability selection stability-selection is a Python implementation of the stability
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly.
Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm
Deep and online learning with spiking neural networks in Python
Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear
Tensorboard for pytorch (and chainer, mxnet, numpy, ...)
tensorboardX Write TensorBoard events with simple function call. The current release (v2.3) is tested on anaconda3, with PyTorch 1.8.1 / torchvision 0
Current state of supervised and unsupervised depth completion methods
Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv
Katana project is a template for ASAP 🚀 ML application deployment
Katana project is a FastAPI template for ASAP 🚀 ML API deployment
A high-performance topological machine learning toolbox in Python
giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G
Single-Cell Analysis in Python. Scales to 1M cells.
Scanpy – Single-Cell Analysis in Python Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It inc
Streamlit — The fastest way to build data apps in Python
Welcome to Streamlit 👋 The fastest way to build and share data apps. Streamlit lets you turn data scripts into sharable web apps in minutes, not week
The purpose of this project is to share knowledge on how awesome Streamlit is and can be
Awesome Streamlit The fastest way to build Awesome Tools and Apps! Powered by Python! The purpose of this project is to share knowledge on how Awesome
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.
An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu
Scikit-Garden or skgarden is a garden for Scikit-Learn compatible decision trees and forests.
Scikit-Garden or skgarden (pronounced as skarden) is a garden for Scikit-Learn compatible decision trees and forests.
InfiniteBoost: building infinite ensembles with gradient descent
InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
A fast, efficient universal vector embedding utility package.
Magnitude: a fast, simple vector embedding utility library A feature-packed Python package and vector storage file format for utilizing vector embeddi
ETNA – time series forecasting framework
ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an
Python module for data science and machine learning users.
dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu
A Powerful Serverless Analysis Toolkit That Takes Trial And Error Out of Machine Learning Projects
KXY: A Seemless API to 10x The Productivity of Machine Learning Engineers Documentation https://www.kxy.ai/reference/ Installation From PyPi: pip inst
An Active Automata Learning Library Written in Python
AALpy An Active Automata Learning Library AALpy is a light-weight active automata learning library written in pure Python. You can start learning auto
ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T
Neural networks applied in recognizing guitar chords using python, AutoML.NET with C# and .NET Core
Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows
Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data 🌈
Rainbow 🌈 An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat
Deep Learning with PyTorch made easy 🚀 !
Deep Learning with PyTorch made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c
A GPU-optional modular synthesizer in pytorch, 16200x faster than realtime, for audio ML researchers.
torchsynth The fastest synth in the universe. Introduction torchsynth is based upon traditional modular synthesis written in pytorch. It is GPU-option
Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.
lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo
Management of exclusive GPU access for distributed machine learning workloads
TensorHive is an open source tool for managing computing resources used by multiple users across distributed hosts. It focuses on granting
Convert Text-to Handwriting Using Python
Convert Text-to Handwriting Using Python Description In this project we'll use python library that's "pywhatkit" for converting text to handwriting. t
Stanza: A Python NLP Library for Many Human Languages
Official Stanford NLP Python Library for Many Human Languages
A crash course in six episodes for software developers who want to become machine learning practitioners.
Featured code sample tensorflow-planespotting Code from the Google Cloud NEXT 2018 session "Tensorflow, deep learning and modern convnets, without a P
Utilities for preprocessing text for deep learning with Keras
Note: This utility is really old and is no longer maintained. You should use keras.layers.TextVectorization instead of this. Utilities for pre-process
How to use TensorLayer
How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay
AutoML library for deep learning
Official Website: autokeras.com AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras
Code for the TCAV ML interpretability project
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim, Martin Wattenberg, Justin Gilmer, C
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
zeus is a Python implementation of the Ensemble Slice Sampling method.
zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl