An edition of Python machine learning (2015)

Python Machine Learning

Learn How to Build Powerful Python Machine Learning Algorithms to Generate Useful Data Insights with This Data Analysis Tutorial

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Python Machine Learning
Sebastian Raschka
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Last edited by ImportBot
December 20, 2023 | History
An edition of Python machine learning (2015)

Python Machine Learning

Learn How to Build Powerful Python Machine Learning Algorithms to Generate Useful Data Insights with This Data Analysis Tutorial

  • 0 Ratings
  • 28 Want to read
  • 1 Currently reading
  • 1 Have read

Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data -- its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Pylearn2, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.

Publish Date
Language
English
Pages
456

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Previews available in: English

Edition Availability
Cover of: Python Machine Learning
Python Machine Learning
Feb 21, 2019, Marcombo
paperback
Cover of: Python Machine Learning
Cover of: Python Machine Learning
Cover of: Python machine learning

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Book Details


The Physical Object

Pagination
454
Number of pages
456

ID Numbers

Open Library
OL39337933M
ISBN 13
9781783555147

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December 20, 2023 Edited by ImportBot import existing book
August 18, 2022 Created by ImportBot Imported from Better World Books record