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Introduction to Machine Learning with scikit-learn

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Introduction

1. What is Machine Learning, and how does it work?

2. Setting up Python for Machine Learning: scikit-learn and Jupyter Notebook

3. Getting started in scikit-learn with the famous iris dataset

4. Training a Machine Learning model with scikit-learn

5. Comparing Machine Learning models in scikit-learn

Intermission

6. Data science pipeline: pandas, seaborn, scikit-learn

7. Cross-validation for parameter tuning, model selection, and feature selection

8. Efficiently searching for optimal tuning parameters

9. Evaluating a classification model

10. Building a Machine Learning workflow

Conclusion