Hyperparameter Optimization with Optuna

In this hands-on tutorial, we’ll dive deep into the fascinating world of hyperparameter optimization using Optuna, a powerful Python library. Buckle up, because we’re about to embark on a journey that will elevate your machine learning models to new heights!

The implementation is available below:

portfolio/hypertune/optuna.ipynb at main · smortezah/portfolio

Table of Contents

1. Introduction
2. Setting Up Your Environment
3. Defining Your Objective Function
4. Exploring Search Spaces
5. Optimization Algorithms
6. Trials, Trials, Trials!
7. Visualizing Results
8. Conclusion and Next Steps

So, grab your favorite beverage, open your code editor, and let’s unlock the secrets of hyperparameter optimization together!

1. Introduction

What exactly are hyperparameters, and why should you care? Let’s unravel this mystery.