Machine Learning with Python: A Practical Beginners' Guide (Machine Learning From Scratch Book 2)

Machine Learning with Python: A Practical Beginners' Guide (Machine Learning From Scratch Book 2)

Product ID: B07WN1TV57 Condition: USED (All books in used condition)

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The item shows wear from consistent use but remains in good condition. It may arrive with damaged packaging or be repackaged.

Machine Learning with Python: A Practical Beginners' Guide (Machine Learning From Scratch Book 2)

As the second title in the Machine Learning for Beginners series, this book teaches beginners to code basic machine learning models using Python. The book is designed for beginners with basic background knowledge of machine learning, including common algorithms such as logistic regression and decision trees. If this doesn’t describe your experience or if you need a refresher, key concepts from machine learning in the opening chapter and there are overviews of specific algorithms dispersed throughout this book. For a gentle and more detailed explanation of machine learning theory minus the code, I suggest reading the first book in this series Machine Learning for Absolute Beginners (Second Edition), which is written for a more general audience.

In this step-by-step guide you will learn:
- To code practical machine learning prediction models using a range of supervised learning algorithms including logistic regression, gradient boosting, and decision trees
- Clean and inspect your data using free machine learning libraries
- Visualize relationships in your dataset including Heatmaps and Pairplots using just a few lines of simple code
- Develop your expertise in managing data using Python

Please feel welcome to join this introductory course by buying a copy, or sending a free sample to your chosen device.

Technical Specifications

Country
USA
Author
Oliver Theobald
Binding
Kindle Edition
Edition
1
Format
Kindle eBook
IsAdultProduct
0
Label
Scatterplot Press
Manufacturer
Scatterplot Press
NumberOfPages
153
PublicationDate
2019-08-15
Publisher
Scatterplot Press
ReleaseDate
2019-08-15
Studio
Scatterplot Press