Machine Learning Algorithms (Packt)
Wednesday, 03 January 2018

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?



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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