Machine learning in Python essential techniques for predictive analysis
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...
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| Format: | Book |
| Language: | English |
| Published: |
Indianapolis, IN
Wiley
[2015]
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| 020 | |a 9781118961742 | ||
| 020 | |z 9781118961766 (electronic bk.) | ||
| 020 | |z 9781118961759 (electronic bk.) | ||
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| 040 | |a UPNM |b eng |c UPNM |e rda | ||
| 090 | |a Q 325.5 |b .B695 2015 | ||
| 100 | 1 | |a Bowles, Michael |e author | |
| 245 | 1 | |a Machine learning in Python |b essential techniques for predictive analysis |c Michael Bowles | |
| 264 | 1 | |a Indianapolis, IN |b Wiley |c [2015] | |
| 264 | 4 | |c ©2015 | |
| 300 | |a xxix, 326 pages |b illustrations |c 24 cm | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a unmediated |2 rdamedia | ||
| 338 | |a volume |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index | ||
| 505 | 0 | |a The Two Essential Algorithms for Making Predictions -- Understand the Problem by Understanding the Data -- Predictive Model Building: Balancing Performance, Complexity, and Big Data -- Penalized Linear Regression -- Building Predictive Models Using Penalized Linear Methods -- Ensemble Methods -- Building Ensemble Models with Python | |
| 520 | |a 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. | ||
| 592 | |a 00101/HL/2019 (750) |b 19/9/2019 |c RM224.68 |h Han Lin Books | ||
| 650 | 0 | |a Machine learning | |
| 650 | 0 | |a Python (Computer program language) | |
| 999 | |a vtls000063132 |c 50721 |d 50721 | ||