Mathematics and R programming for machine learning : from the ground up /

Bibliographic Details
Main Author:	Claster, William B. (Author)
Corporate Author:	ProQuest (Firm)
Format:	eBook
Language:	English
Published:	Boca Raton : CRC Press, 2020.
Subjects:	Machine learning. R (Computer program language) Programming (Mathematics) Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

<P>Chapter 1. Functions Tutorial. Chapter 2. Logic and R. Chapter 3. Sets with R: Building the Tools. Chapter 4. Probability. Chapter 5. NaiÌˆve Rule. Chapter 6. Complete Bayes. Chapter 7. NaiÌˆve Bayes Classifier. Chapter 8. Stored Model for Naive Bayes Classifier. Chapter 9. Review of Mathematics for Neural Networks. Chapter 10. Calculus. Chapter 11. Neural Networks
Feed Forward Process and Back Propagation Process. Chapter 12. Programming a Neural Network using OOP in R. Chapter 13. Adding in a Bias Term. Chapter 14. Modular Version of Neural Networks for Deep Learning. Chapter 15. Deep Learning with Convolutional Neural Networks. Chapter 16. R Packages for Neural Networks, Deep Learning, and NaiÌˆve Bayes.</P>