Sklearn-Introduction-Guide

This code goes along with the Algotrading101 article about Sklearn (scikit-learn)

Table of contents

1. What is Sklearn?
2. What is Sklearn used for?
3. How to download Sklearn for Python?
4. How to pick the best scikit-learn model?
5. Sklearn preprocessing – Prepare the data for analysis
   1. Sklearn feature encoding
   2. Sklearn data scaling
   3. Sklearn missing values
   4. Sklearn train test split
6. Sklearn Regression – Predict the future
   1. Sklearn Linear Regression
   2. Other Sklearn regression models
7. Sklearn Classification – Did I just see a cat?
   1. Sklearn Decision Tree Classifier
   2. Other Sklearn classification models
8. Sklearn Clustering – Create groups of similar data
   1. Sklearn DBSCAN
   2. Other Sklearn clustering models
9. Sklearn Dimensionality Reduction – Reducing random variables
   1. Sklearn PCA
   2. Other Sklearn Dimensionality Reduction models
10. What are the 3 Common Machine Learning Analysis/Testing Mistakes?
11. Full code

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Info

Author	Igor Radovanovic
Published	May 14, 2021