
Building Machine Learning Systems with Python
Building Machine Learning Systems with Python
Packt Publishing
Published on 26. March 2015
Book
Paperback/Softback
326 pages
978-1-78439-277-2 (ISBN)
Description
Key Features
Book DescriptionWhat you will learn
Who this book is for
Book DescriptionWhat you will learn
Who this book is for
More details
Edition
Second Edition
Language
English
Place of publication
Birmingham
United Kingdom
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 18 mm
Weight
611 gr
ISBN-13
978-1-78439-277-2 (9781784392772)
Schweitzer Classification
Persons
Luis Pedro Coelho is a computational biologist who analyzes DNA from microbial communities to characterize their behavior. He has also worked extensively in bioimage informatics - the application of machine learning techniques for the analysis of images of biological specimens. His main focus is on the processing and integration of large-scale datasets. He has a PhD from Carnegie Mellon University and has authored several scientific publications. In 2004, he began developing in Python and has contributed to several open source libraries. He is currently a faculty member at Fudan University in Shanghai. Willi Richert is a Software Development Engineer at Microsoft for the last 5 years. He has also worked as a project team leader for mobile devices (Java/Python) at Richert GbR.
Content
Table of Contents
Getting Started with Python Machine Learning
Classifying with Real-world Examples
Clustering ? Finding Related Posts
Topic Modeling
Classification ? Detecting Poor Answers
Classification II ? Sentiment Analysis
Regression
Regression ? Recommendations Improved
Classification III ? Music Genre Classification
Computer Vision ? Pattern Recognition
Dimensionality Reduction
Big(ger) Data
Appendix: Where to Learn More about Machine Learning
Getting Started with Python Machine Learning
Classifying with Real-world Examples
Clustering ? Finding Related Posts
Topic Modeling
Classification ? Detecting Poor Answers
Classification II ? Sentiment Analysis
Regression
Regression ? Recommendations Improved
Classification III ? Music Genre Classification
Computer Vision ? Pattern Recognition
Dimensionality Reduction
Big(ger) Data
Appendix: Where to Learn More about Machine Learning