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
Date: July 2017
Audience: IT professionals
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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