Machine Learning in Python

Essential Techniques for Predictive Analysis

Nonfiction, Computers, Advanced Computing, Theory, Artificial Intelligence, Programming, Programming Languages
Cover of the book Machine Learning in Python by Michael Bowles, Wiley
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Michael Bowles ISBN: 9781118961759
Publisher: Wiley Publication: March 31, 2015
Imprint: Wiley Language: English
Author: Michael Bowles
ISBN: 9781118961759
Publisher: Wiley
Publication: March 31, 2015
Imprint: Wiley
Language: English

Learn a simpler and more effective way to analyze data and predict outcomes with Python

Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions.

Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language.

  • Predict outcomes using linear and ensemble algorithm families
  • Build predictive models that solve a range of simple and complex problems
  • Apply core machine learning algorithms using Python
  • Use sample code directly to build custom solutions

Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Learn a simpler and more effective way to analyze data and predict outcomes with Python

Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions.

Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language.

Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics.

More books from Wiley

Cover of the book Enzyme Regulation in Metabolic Pathways by Michael Bowles
Cover of the book Paediatrics by Michael Bowles
Cover of the book Veterans and Active Duty Military Psychotherapy Homework Planner by Michael Bowles
Cover of the book Mechanical Measurements by Michael Bowles
Cover of the book Windows Home Server For Dummies by Michael Bowles
Cover of the book The CompleteLandlord.com Ultimate Real Estate Investing Handbook by Michael Bowles
Cover of the book King's Applied Anatomy of the Central Nervous System of Domestic Mammals by Michael Bowles
Cover of the book Foundations of Forensic Document Analysis by Michael Bowles
Cover of the book Asia-Pacific Transfer Pricing Handbook by Michael Bowles
Cover of the book Life Cycle Assessment of Energy Systems by Michael Bowles
Cover of the book African Americans in the Colonial Era by Michael Bowles
Cover of the book Arts Marketing Insights by Michael Bowles
Cover of the book The Media and The Public by Michael Bowles
Cover of the book Transformers and Inductors for Power Electronics by Michael Bowles
Cover of the book Information, Technology, and Innovation by Michael Bowles
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy