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1. Introduction.ipynb
1. Introduction.ipynb
 
 
10. Cross Validation and Model Selection.ipynb
10. Cross Validation and Model Selection.ipynb
 
 
11. Hyperparameter Tuning.ipynb
11. Hyperparameter Tuning.ipynb
 
 
12. Preprocessing.ipynb
12. Preprocessing.ipynb
 
 
13. Feature extraction.ipynb
13. Feature extraction.ipynb
 
 
14. Machine Learning Process.ipynb
14. Machine Learning Process.ipynb
 
 
2. Setup and Benefits of Scikit Learn.ipynb
2. Setup and Benefits of Scikit Learn.ipynb
 
 
3. Training a model on the Iris Dataset.ipynb
3. Training a model on the Iris Dataset.ipynb
 
 
4. Training, Testing Datasets.ipynb
4. Training, Testing Datasets.ipynb
 
 
5. Classification Algorithms.ipynb
5. Classification Algorithms.ipynb
 
 
6. Regression Algorithms.ipynb
6. Regression Algorithms.ipynb
 
 
7. Clustering Algorithms.ipynb
7. Clustering Algorithms.ipynb
 
 
8. Dimensionality Reduction.ipynb
8. Dimensionality Reduction.ipynb
 
 
9. Dimensionality Reduction 2.ipynb
9. Dimensionality Reduction 2.ipynb
 
 
README.md
README.md
 
 

README.md

Scikit Learn Tutorial

Scikit Learn Logo

This repository contains the notebooks for my Scikit Learn Tutorial Series. In the series I cover what Scikit Learn is, how it works and how it can be used.

Getting Started

Clone the repository run jupyter notebook

Prerequisites

Open 2. Setup and Benefits of Scikit Learn to see how to install all you need.

Author

Gilbert Tanner