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 Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, Methodology by Michael Bowles
Cover of the book Tyson by Michael Bowles
Cover of the book Windows 10 für Dummies by Michael Bowles
Cover of the book Synthetic Natural Gas by Michael Bowles
Cover of the book Cyberbullying by Michael Bowles
Cover of the book Die 12 Lektionen zur Führung im Change Management by Michael Bowles
Cover of the book From 0 to 130 Properties in 3.5 Years by Michael Bowles
Cover of the book Correspondence Analysis by Michael Bowles
Cover of the book Noise Control by Michael Bowles
Cover of the book Family History for the Older and Wiser by Michael Bowles
Cover of the book Diamonds by Michael Bowles
Cover of the book Applied Integer Programming by Michael Bowles
Cover of the book Chemesthesis by Michael Bowles
Cover of the book ESD Basics by Michael Bowles
Cover of the book Raising Capital For Dummies 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