Mathematics and R programming for machine learning : from the ground up /: from the ground up. (2020)

• Record Type: Book
• Further Information: Note: William B. Claster.
• Authors: Claster, William B
• Contents: Chapter 1. Functions Tutorial. Chapter 2. Logic and R. Chapter 3. Sets with R: Building the Tools. Chapter 4. Probability. Chapter 5. Naïve Rule. Chapter 6. Complete Bayes. Chapter 7. Naïve 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 Naïve Bayes.
• Edition: 1st
• Publisher Details: Boca Raton : CRC Press
• Publication Date: 2020
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 006.31; Machine learning; R (Computer program language); Programming (Mathematics)
• Languages: English
• ISBNs: 9781000196993; 9781000196979; 9781000196986; 9781003051220
• Related ISBNs: 9780367561949; 9780367507855
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.