Dr. Vahid Mirjalili is a data scientist with a diverse background in engineering, mathematics, and computer science. With his specialty in data mining, he is very interested in predictive modeling and getting insights from data. Currently, he is working towards publishing a book on big data analysis, which covers a wide range of tools and techniques for analyzing massive data sets. Furthermore, as a Python developer, he likes to contribute to the open source community. He has developed Python packages for data clustering, such as PyClust. A collection of his tutorials and programs on data science can be found in his Github repository at http://github.com/mirjalil/DataScience. For more information, please visit his personal website at http://vahidmirjalili.com.
Designing Machine Learning Systems with Python
By :
Designing Machine Learning Systems with Python
By:
Overview of this book
Machine learning is one of the fastest growing trends in modern computing. It has applications in a wide range of fields, including economics, the natural sciences, web development, and business modeling. In order to harness the power of these systems, it is essential that the practitioner develops a solid understanding of the underlying design principles.
There are many reasons why machine learning models may not give accurate results. By looking at these systems from a design perspective, we gain a deeper understanding of the underlying algorithms and the optimisational methods that are available. This book will give you a solid foundation in the machine learning design process, and enable you to build customised machine learning models to solve unique problems. You may already know about, or have worked with, some of the
off-the-shelf machine learning models for solving common problems such as spam detection or movie classification, but to begin solving more complex problems, it is important to adapt these models to your own specific needs. This book will give you this understanding and more.
Table of Contents (16 chapters)
Designing Machine Learning Systems with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Free Chapter
Thinking in Machine Learning
Tools and Techniques
Turning Data into Information
Models – Learning from Information
Linear Models
Neural Networks
Features – How Algorithms See the World
Learning with Ensembles
Design Strategies and Case Studies
Index
Customer Reviews