model-selection
There are 368 repositories under model-selection topic.
ray-project/ray
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.
EpistasisLab/tpot
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
DistrictDataLabs/yellowbrick
Visual analysis and diagnostic tools to facilitate machine learning model selection.
rorysroes/SGX-Full-OrderBook-Tick-Data-Trading-Strategy
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
balavenkatesh3322/CV-pretrained-model
A collection of computer vision pre-trained models.
DeepWisdom/AutoDL
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.
sberbank-ai-lab/LightAutoML
LAMA - automatic model creation framework
alteryx/evalml
EvalML is an AutoML library written in python.
smartcorelib/smartcore
A comprehensive library for machine learning and numerical computing. The library provides a set of tools for linear algebra, numerical computing, optimization, and enables a generic, powerful yet still efficient approach to machine learning.
Western-OC2-Lab/AutoML-Implementation-for-Static-and-Dynamic-Data-Analytics
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
cerlymarco/shap-hypetune
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
BCG-X-Official/facet
Human-explainable AI.
SimonBlanke/Hyperactive
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
yzkang/My-Data-Competition-Experience
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
joshspeagle/dynesty
Dynamic Nested Sampling package for computing Bayesian posteriors and evidences
rodrigo-arenas/Sklearn-genetic-opt
ML hyperparameters tuning and features selection, using evolutionary algorithms.
WenjieZ/TSCV
Time Series Cross-Validation -- an extension for scikit-learn
Alex-Lekov/AutoML_Alex
State-of-the art Automated Machine Learning python library for Tabular Data
Cibiv/IQ-TREE
Efficient phylogenomic software by maximum likelihood
EpistasisLab/tpot2
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
heidelbergcement/hcrystalball
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
IngoScholtes/pathpy
pathpy is an OpenSource python package for the modeling and analysis of pathways and temporal networks using higher-order and multi-order graphical models
christophmark/bayesloop
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
JohannesBuchner/UltraNest
Fit and compare complex models reliably and rapidly. Advanced nested sampling.
tlverse/sl3
💪 🤔 Modern Super Learning with Machine Learning Pipelines
metriculous-ml/metriculous
Measure and visualize machine learning model performance without the usual boilerplate.
automix-llm/automix
Mixing Language Models with Self-Verification and Meta-Verification
maxim5/hyper-engine
Python library for Bayesian hyper-parameters optimization
alessandrolulli/reforest
Random Forests in Apache Spark
BCG-X-Official/sklearndf
DataFrame support for scikit-learn.
junipertcy/bipartiteSBM
A Bayesian model+algorithm for community detection in bipartite networks
mononitogoswami/tsad-model-selection
Code for "Unsupervised Model Selection for Time-series Anomaly Detection", ICLR 2023.
serodriguez68/designing-ml-systems-summary
A detailed summary of "Designing Machine Learning Systems" by Chip Huyen. This book gives you and end-to-end view of all the steps required to build AND OPERATE ML products in production. It is a must-read for ML practitioners and Software Engineers Transitioning into ML.
JohannesBuchner/BXA
Bayesian X-ray analysis (nested sampling for Xspec and Sherpa)
LFhase/PAIR
[ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
eaglewarrior/Machine-learning
This repository will contain all the stuffs required for beginners in ML and DL do follow and star this repo for regular updates