1430 Repositories
Python state-of-the-art-models Libraries
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Deep recommender models using PyTorch.
Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various poin
A Python Library for Simple Models and Containers Persisted in Redis
Redisco Python Containers and Simple Models for Redis Description Redisco allows you to store objects in Redis. It is inspired by the Ruby library Ohm
Magenta: Music and Art Generation with Machine Intelligence
Magenta is a research project exploring the role of machine learning in the process of creating art and music. Primarily this involves developing new
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
Colibri core is an NLP tool as well as a C++ and Python library for working with basic linguistic constructions such as n-grams and skipgrams (i.e patterns with one or more gaps, either of fixed or dynamic size) in a quick and memory-efficient way. At the core is the tool ``colibri-patternmodeller`` whi ch allows you to build, view, manipulate and query pattern models.
Colibri Core by Maarten van Gompel, [email protected], Radboud University Nijmegen Licensed under GPLv3 (See http://www.gnu.org/licenses/gpl-3.0.html
Create UIs for prototyping your machine learning model in 3 minutes
Note: We just launched Hosted, where anyone can upload their interface for permanent hosting. Check it out! Welcome to Gradio Quickly create customiza
Automates Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning :rocket:
MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents
Machine learning, in numpy
numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens
Turi Create simplifies the development of custom machine learning models.
Quick Links: Installation | Documentation | WWDC 2019 | WWDC 2018 Turi Create Check out our talks at WWDC 2019 and at WWDC 2018! Turi Create simplifie
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Machine Learning From Scratch About Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose
Toolbox of models, callbacks, and datasets for AI/ML researchers.
Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch Website • Installation • Main
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 •
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit
Fast, flexible and easy to use probabilistic modelling in Python.
Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic
pyhsmm - library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and explicit-duration Hidden semi-Markov Models (HSMMs), focusing on the Bayesian Nonparametric extensions, the HDP-HMM and HDP-HSMM, mostly with weak-limit approximations.
Bayesian inference in HSMMs and HMMs This is a Python library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and expli
Easy and comprehensive assessment of predictive power, with support for neuroimaging features
Documentation: https://raamana.github.io/neuropredict/ News As of v0.6, neuropredict now supports regression applications i.e. predicting continuous t
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Auto-ViML Automatically Build Variant Interpretable ML models fast! Auto_ViML is pronounced "auto vimal" (autovimal logo created by Sanket Ghanmare) N
a delightful machine learning tool that allows you to train, test and use models without writing code
igel A delightful machine learning tool that allows you to train/fit, test and use models without writing code Note I'm also working on a GUI desktop
💡 Learnergy is a Python library for energy-based machine learning models.
Learnergy: Energy-based Machine Learners Welcome to Learnergy. Did you ever reach a bottleneck in your computational experiments? Are you tired of imp
Quickly and easily create / train a custom DeepDream model
Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat
Build fully-functioning computer vision models with PyTorch
Detecto is a Python package that allows you to build fully-functioning computer vision and object detection models with just 5 lines of code. Inferenc
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl
Computer art based on quadtrees.
Quads Computer art based on quadtrees. The program targets an input image. The input image is split into four quadrants. Each quadrant is assigned an
Hook and simulate global keyboard events on Windows and Linux.
keyboard Take full control of your keyboard with this small Python library. Hook global events, register hotkeys, simulate key presses and much more.
A Django application that provides country choices for use with forms, flag icons static files, and a country field for models.
Django Countries A Django application that provides country choices for use with forms, flag icons static files, and a country field for models. Insta
:art: Diagram as Code for prototyping cloud system architectures
Diagrams Diagram as Code. Diagrams lets you draw the cloud system architecture in Python code. It was born for prototyping a new system architecture d
Automatic caching and invalidation for Django models through the ORM.
Cache Machine Cache Machine provides automatic caching and invalidation for Django models through the ORM. For full docs, see https://cache-machine.re
A lightweight, object-oriented finite state machine implementation in Python with many extensions
transitions A lightweight, object-oriented state machine implementation in Python with many extensions. Compatible with Python 2.7+ and 3.0+. Installa