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Python Machine Learning Case Studies

Language EnglishEnglish
Book Paperback
Book Python Machine Learning Case Studies Danish Haroon
Libristo code: 16096861
Publishers APress, October 2017
Embrace machine learning approaches and Python to enable automatic rendering of rich insights and so... Full description
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59.53 €
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Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources. 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 presented. 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 book is 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 concepts Work on real-world applications of machine learningLearn concepts of model selection and optimizationGet 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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About the book

Full name Python Machine Learning Case Studies
Author Danish Haroon
Language English
Binding Book - Paperback
Date of issue 2017
Number of pages 204
EAN 9781484228227
ISBN 1484228227
Libristo code 16096861
Publishers APress
Weight 472
Dimensions 155 x 235 x 13
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