This guide to machine learning takes a solid, concept-rich, yet highly practical approach. Author Giuseppe Bonaccorso covers the whats and whys of machine learning algorithms and their implementation. The book is aimed at IT professionals who want to enter the field of data science and are very new to machine learning. Familiarity with languages such as R and Python will be invaluable.
<ASIN:1785889621>
Author: Giuseppe Bonaccorso Publisher: Packt Date: July 2017 Pages: 360 ISBN: 978-1785889622 Print: 1785889621 Kindle: B072QBG11J Audience: IT professionals Level: Intermediate Category: Artificial Intelligence
- Acquaint yourself with important elements of Machine Learning
- Understand the feature selection and feature engineering process
- Assess performance and error trade-offs for Linear Regression
- Build a data model and understand how it works by using different types of algorithm
- Learn to tune the parameters of Support Vector machines
- Implement clusters to a dataset
- Explore the concept of Natural Processing Language and Recommendation Systems
- Create a ML architecture from scratch.
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Modern Software Engineering (Addison-Wesley)
Author: David Farley Pages: 256 ISBN: 978-0137314911 Print:0137314914 Kindle: B09GG6XKS4 Audience: Software Engineers Rating: 3.5 Reviewer: Kay Ewbank
This book is subtitled 'doing what works to build better software faster' - does it teach you how to achieve that?
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Reliable Source: Lessons from a Life in Software Engineering
Author: James Bonang Date: January 2022 Pages: 608 Kindle: B09QCBVJ9V Audience: General interest Rating: 5 Reviewer: Kay Ewbank
This book combines a fun read with interesting insights into how to write reliable programs.
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