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.

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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Object-Oriented Python

Author: Irv Kalb
Publisher: No Starch Press
Date: January 2022
Pages: 416
ISBN: 978-1718502062
Print: 1718502060
Kindle: ‎ B0957SHYQL
Audience: Python developers
Rating: 3
Reviewer: Mike James
Python, Object-Oriented? Not a lot of programmers know that!



Deep Learning (No Starch Press)

Author: Andrew Glassner
Publisher: No Starch Press
Date: July 2021
Pages: 750
ISBN: 978-1718500723
Print: 1718500726
Kindle: ‎ B085BVWXNS
Audience: Developers interested in deep learning
Rating: Mike James
Reviewer: 5
A book on deep learning wtihout an equation in sight?


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