/hyperparameter-optimization

Code repository for the online course Hyperparameter Optimization for Machine Learning

Primary LanguageJupyter NotebookOtherNOASSERTION

PythonVersion License https://github.com/solegalli/hyperparameter-optimization/blob/master/LICENSE Sponsorship https://www.trainindata.com/

Hyperparameter tuning for Machine Learning - Code Repository

Published May, 2021

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Table of Contents

  1. Cross-Validation

    1. K-fold, LOOCV, LPOCV, Stratified CV
    2. Group CV and variants
    3. CV for time series
    4. Nested CV

  2. Basic Search Algorithms

    1. Manual Search, Grid Search and Random Search

  3. Bayesian Optimization

    1. with Gaussian Processes
    2. with Random Forests (SMAC) and GBMs
    3. with Parzen windows (Tree-structured Parzen Estimators or TPE)

  4. Multi-fidelity Optimization

    1. Successive Halving
    2. Hyperband
    3. BOHB

  5. Other Search Algorthms

    1. Simulated Annealing
    2. Population Based Optimization

  6. Gentetic Algorithms

    1. CMA-ES

  7. Python tools

    1. Scikit-learn
    2. Scikit-optimize
    3. Hyperopt
    4. Optuna
    5. Keras Tuner
    6. SMAC
    7. Others