Packt Publishing, 2017. — 449 p. — ISBN: 978-1785889622.
Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide
About This BookGet started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide.
Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation.
Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide.
Who This Book Is ForThis book is for 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 here.
What You Will LearnAcquaint 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.