With machine learning techniques and R, you can easily develop these kinds of applications in an efficient way. Practical Machine Learning with R begins by helping you grasp the basics of machine learning methods, while also highlighting how and why they work. (Limited-time offer)
Table of Contents
- An Introduction to Machine Learning
- Data Cleaning and Pre-processing
- Feature Engineering
- Introduction to neuralnet and Evaluation Methods
- Linear and Logistic Regression Models
- Unsupervised Learning
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Author(s): Brindha Priyadarshini Jeyaraman, Ludvig Renbo Olsen, Monicah Wambugu
Publisher: Packt Publishing
Published: August 2019
Format(s): Online
File size: –
Number of pages: 416
Download / View Link(s): This offer has ended.
Free as of 05/04/2023.
Publisher: Packt Publishing
Published: August 2019
Format(s): Online
File size: –
Number of pages: 416
Download / View Link(s): This offer has ended.
Free as of 05/04/2023.