AI Features

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Introduction

Course Overview Introduction to Hyperparameters Introduction to Hyperparameter Optimization Introduction to the Dataset for the Course

Random Search Method

Introduction to the Random Search Method How Does Random Search Work Data Preparation Random Search Using Logistic Regression Random Search Using the Random Forest Algorithm Advantages and Disadvantages of Random Search Method Quiz on Random Search Method

Grid Search Method

Introduction to Grid Search Method How Does Grid Search Work Grid Search Using Logistic Regression Grid Search Using Random Forest Algorithm Advantages and Disadvantages of the Grid Search Method Quiz on Grid Search Method

Sequential Model-Based Optimization Method

Introduction to the Sequential Model-Based Optimization Method How Does Sequential Model-Based Optimisation Work Sequential Model-Based Optimization using K-Nearest Neighbors SMBO Using Histogram-Based Gradient Boosting Advantages and Disadvantages of the SMBO Method Quiz on the Sequential Model-Based Optimization Method

Tree-Structured Parzen Estimators Method

Introduction to the Tree-Structured Parzen Estimator Method How Does the Tree-Structured Parzen Estimator Method Work Tree-Structured Parzen Estimator Method Using KNN TSPE Method Using Histogram-Based Gradient Boosting Advantages and Disadvantages of the TSPE Method Quiz on the Tree-Structured Parzen Estimator (TPE) Method

Genetic Algorithm

Introduction to the Genetic Algorithm How Does the Genetic Algorithm Work Genetic Algorithm Using the KNN Model Genetic Algorithm Using Random Forest Advantages and Disadvantages of the Genetic Algorithm Quiz on Genetic Algorithm

Course Assessment

Evaluate Hyperparameter Optimization Concepts

Mini Project

Optimizing ML Model for Promotion Selection

Conclusion

Appendix

Set Up the Computer and Install Python Packages

Project

Predict Cancer Using Machine Learning Models

Mastering Hyperparameter Optimization for Machine Learning

Final Remarks

Let's summarize what we have learned in this course.

We'll cover the following...

Highlights
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