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Machine Learning with Scikit-Learn

via LinkedIn Learning

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Overview

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Learn to use scikit-learn, the popular open-source Python library, to build efficient machine learning models.

Syllabus

Introduction

Effective machine learning with scikit-learn
What you should know before you start
Using the exercise files

1. Input and Loading Data

What is machine learning?
Why use scikit-learn for machine learning?

2. Supervised Learning

What is supervised learning?
How to format data for scikit-learn
Linear regression using scikit-learn
Train test split
Logistic regression using scikit-learn
Logistic regression for multiclass classification
Decision trees using scikit-learn
How to visualize decision trees using Matplotlib
Bagged trees using scikit-learn
Random forests using scikit-learn
Which machine learning model should you use?

3. Unsupervised Learning

What is unsupervised learning?
K-means clustering
Principal component analysis (PCA) for data visualization
PCA to speed up machine learning algorithms
scikit-learn pipelines

Conclusion

Get started with scikit-learn

Taught by

Michael Galarnyk and Madecraft

Reviews

4.5 rating at LinkedIn Learning based on 738 ratings

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