#Model-selection
Showing 23 of 23 repositories tagged #model-selection, ranked by stars
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
A collection of computer vision pre-trained models.
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.
A comprehensive library for machine learning and numerical computing. Apply Machine Learning with Rust leveraging first principles.
LAMA - automatic model creation framework
EvalML is an AutoML library written in python.
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
A unified interface for optimization algorithms and experiments
Human-explainable AI.
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
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Make your OpenClaw AI agent faster, smarter, and cheaper. Speed optimization, memory architecture, context management, model selection, and one-shot development guide.
Time Series Cross-Validation -- an extension for scikit-learn
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
State-of-the art Automated Machine Learning python library for Tabular Data
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.
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
Measure and visualize machine learning model performance without the usual boilerplate.
Python library for Bayesian hyper-parameters optimization
Code for "Unsupervised Model Selection for Time-series Anomaly Detection", ICLR 2023.
DataFrame support for scikit-learn.