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39 search results found

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Yellowbrick ⭐ 4,102

Visual analysis and diagnostic tools to facilitate machine learning model selection.

Sgx Full Orderbook Tick Data Trading Strategy ⭐ 1,151

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.

Cv Pretrained Model ⭐ 991

A collection of computer vision pre-trained models.

Lightautoml ⭐ 769

LAMA - automatic model creation framework

EvalML is an AutoML library written in python.

Human-explainable AI.

Hyperactive ⭐ 475

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

Dynesty ⭐ 323

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

My Data Competition Experience ⭐ 271

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

Sklearn Genetic Opt ⭐ 236

ML hyperparameters tuning and features selection, using evolutionary algorithms.

Time Series Cross-Validation -- an extension for scikit-learn

Automl_alex ⭐ 171

State-of-the art Automated Machine Learning python library for Tabular Data

Hcrystalball ⭐ 135

A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.

Bayesloop ⭐ 127

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

Ultranest ⭐ 119

Fit and compare complex models reliably and rapidly. Advanced nested sampling.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

pathpy is an OpenSource python package for the modeling and analysis of pathways and temporal networks using higher-order and multi-order graphical models

Metriculous ⭐ 94

Measure and visualize machine learning model performance without the usual boilerplate.

Hyper Engine ⭐ 69

Python library for Bayesian hyper-parameters optimization

Sklearndf ⭐ 59

DataFrame support for scikit-learn.

Bayesian X-ray analysis (nested sampling for Xspec and Sherpa)

Bayesianframework ⭐ 31

A framework for Bayesian model selection (BMS) and Bayesian model Averaging (BMA).

Kullback-Leibler projections for Bayesian model selection in Python

skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.

FluidML is a lightweight framework for developing machine learning pipelines.

Cerebro System ⭐ 18

Data System for Optimized Deep Learning Model Selection

Infogan Cr ⭐ 15

InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs, ICML 2020

Lightweight and modular MLOps library targeted at small teams or individuals

[NeurIPS 2023] Official Pytorch code for LOVM: Language-Only Vision Model Selection

Genetics ⭐ 11

Genetic Algorithm in Python, which could be used for Sampling, Feature Select, Model Select, etc in Machine Learning

Pythonbrmltoolbox ⭐ 10

Python 3.7 version of David Barber's MATLAB BRMLtoolbox

Code release for Adversarial Branch Architecture Search for Unsupervised Domain Adaptation

Aind Recognizer ⭐ 10

Term 1 Project 3 Design a Sign Language Recognition System by Luke Schoen for Udacity Artificial Intelligence Nanodegree (AIND)

Home Credit Default Risk ⭐ 9

Predicting how capable each applicant is of repaying a loan (Kaggle Challenge)

Bayesianfridge ⭐ 8

Sequential Monte Carlo sampler for PyMC2 models.

A benchmark suite for Scalable Diverse Model Selection for Accessible Transfer Learning from our NeurIPS 2021 paper.

A toolkit for automatically selecting a suitable classification model along with an assessment of how hard or easy to learn a classifier on the given dataset.

Search for a model and corresponding hyperparameters that best model your data

Modelcreator ⭐ 5

Simple python package for creating predictive models

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