Book Image

Building Machine Learning Systems with Python

Book Image

Building Machine Learning Systems with Python

Overview of this book

Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail. Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques. Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on. Readers will learn how to write programs that classify the quality of StackOverflow answers or whether a music file is Jazz or Metal. They will learn regression, which is demonstrated on how to recommend movies to users. Advanced topics such as topic modeling (finding a text's most important topics), basket analysis, and cloud computing are covered as well as many other interesting aspects.Building Machine Learning Systems with Python will give you the tools and understanding required to build your own systems, which are tailored to solve your problems.
Table of Contents (20 chapters)
Building Machine Learning Systems with Python
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Improving classification performance with Mel Frequency Cepstral Coefficients


We have already learned that FFT is pointing us in the right direction, but in itself it will not be enough to finally arrive at a classifier that successfully manages to organize our scrambled directory containing songs of diverse music genres into individual genre directories. We somehow need a more advanced version of it.

At this point, it is always wise to acknowledge that we have to do more research. Other people might have had similar challenges in the past and already found out new ways that might also help us. And indeed, there is even a yearly conference only dedicated to music genre classification organized by the International Society for Music Information Retrieval (ISMIR). Apparently, Automatic Music Genre Classification (AMGC) is an established subfield of Music Information Retrieval (MIR). Glancing over some of the AMGC papers, we see that there is a bunch of work targeting automatic genre classification...