Overview
- Applies a case study-based approach to machine learning
- Gives you insights into the core concepts of machine learning and optimization techniques
- Uses Python as an aid to implement machine learning
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About this book
Python Machine Learning Case Studies takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You’ll see machine learning techniques that you can use to support your products and services. Moreover you’ll learn the pros and cons of each of the machine learning concepts to help you decide which one best suits your needs.
By taking a step-by-step approach to coding in Python you’ll be able to understand
the rationale behind model selection and decisions within the machine learning process. The bookis equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems.
What You Will Learn
- Gain insights into machine learning conceptsÂ
- Work on real-world applications of machine learning
- Learn concepts of model selection and optimization
- Get a hands-on overview of Python from a machine learning point of view
Who This Book Is For
Data scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.
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Table of contents (5 chapters)
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Bibliographic Information
Book Title: Python Machine Learning Case Studies
Book Subtitle: Five Case Studies for the Data Scientist
Authors: Danish Haroon
DOI: https://doi.org/10.1007/978-1-4842-2823-4
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Danish Haroon 2017
Softcover ISBN: 978-1-4842-2822-7Published: 29 October 2017
eBook ISBN: 978-1-4842-2823-4Published: 27 October 2017
Edition Number: 1
Number of Pages: XVII, 204
Number of Illustrations: 21 b/w illustrations, 99 illustrations in colour
Topics: Artificial Intelligence, Python, Big Data, Programming Languages, Compilers, Interpreters, Programming Techniques, Database Management