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LiYangHart / Hyperparameter-Optimization-of-Machine-Learning-Algorithms

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Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

machine-learning deep-learning random-forest optimization svm genetic-algorithm machine-learning-algorithms hyperparameter-optimization artificial-neural-networks grid-search tuning-parameters knn bayesian-optimization hyperparameter-tuning random-search particle-swarm-optimization hpo python-examples python-samples hyperband
  • Updated Aug 19, 2021
  • Jupyter Notebook

farhanchoudhary / Machine_Learning_A-Z_All_Codes_and_Templates

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All codes, both created and optimized for best results from the SuperDataScience Course

natural-language-processing reinforcement-learning deep-learning clustering cross-validation naive-bayes-classifier thompson-sampling neural-networks classification dimensionality-reduction grid-search principal-component-analysis clustering-algorithm upper-confidence-bounds k-fold xgboost-algorithm association-rule-learning machine-learning-az
  • Updated Nov 5, 2017
  • Python

sourcecode369 / ml-algorithms-on-scikit-and-keras

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Implementation scripts of Machine Learning algorithms on Scikit-learn and Keras for complete novice..

machine-learning natural-language-processing reinforcement-learning deep-learning clustering numpy scikit-learn keras regression pandas xgboost classification dimensionality-reduction matplotlib t-sne data-preprocessing grid-search association-rule-learning kfold-cross-validation multiarm-bandit
  • Updated Jul 22, 2018
  • Jupyter Notebook

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