Supervised Machine Learning with Python will guide you through the implementation and nuances of many popular supervised machine learning algorithms, and help you understand how they work.
You’ll embark on this journey with a quick overview of supervised learning and see how it differs from unsupervised learning. You’ll then explore parametric models, such as linear and logistic regression, non-parametric methods, such as decision trees, and a variety of clustering techniques that facilitate decision-making and predictions.
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Table of Contents
- First Step Towards Supervised Learning
- Implementing Parametric Models
- Working with Non-Parametric Models
- Advanced Topics in Supervised Machine Learning
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Author(s): Taylor Smith
Publisher: Packt Publishing
Published: May 2019
Format(s): Online
File size: –
Number of pages: 162
Download / View Link(s): This offer has ended.
Free as of 12/26/2023.
Publisher: Packt Publishing
Published: May 2019
Format(s): Online
File size: –
Number of pages: 162
Download / View Link(s): This offer has ended.
Free as of 12/26/2023.