Book Image

Building Machine Learning Systems with Python - Third Edition

By : Luis Pedro Coelho, Willi Richert, Matthieu Brucher
Book Image

Building Machine Learning Systems with Python - Third Edition

By: Luis Pedro Coelho, Willi Richert, Matthieu Brucher

Overview of this book

Machine learning enables systems to make predictions based on historical data. Python is one of the most popular languages used to develop machine learning applications, thanks to its extensive library support. This updated third edition of Building Machine Learning Systems with Python helps you get up to speed with the latest trends in artificial intelligence (AI). With this guide’s hands-on approach, you’ll learn to build state-of-the-art machine learning models from scratch. Complete with ready-to-implement code and real-world examples, the book starts by introducing the Python ecosystem for machine learning. You’ll then learn best practices for preparing data for analysis and later gain insights into implementing supervised and unsupervised machine learning techniques such as classification, regression and clustering. As you progress, you’ll understand how to use Python’s scikit-learn and TensorFlow libraries to build production-ready and end-to-end machine learning system models, and then fine-tune them for high performance. By the end of this book, you’ll have the skills you need to confidently train and deploy enterprise-grade machine learning models in Python.
Table of Contents (17 chapters)
Free Chapter
1
Getting Started with Python Machine Learning

Improving classification performance with mel frequency cepstral coefficients

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

At this point, we have to do more research. Other people might have had similar challenges in the past and already found ways that might also help us. And, indeed, there is even a yearly conference 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. Glancing over some of the AMGC papers, we can see that there is a bunch of work targeting automatic...