With Mastering Machine Learning with R – Second Edition, understand the benefits and potential pitfalls of using machine learning methods such as Multi-Class Classification and Unsupervised Learning. Implement advanced concepts in machine learning with this example-rich guide.(Limited-time offer)
Table of Contents
- A Process for Success
- Linear Regression – The Blocking and Tackling of Machine Learning
- Logistic Regression and Discriminant Analysis
- Advanced Feature Selection in Linear Models
- More Classification Techniques – K-Nearest Neighbors and Support Vector Machines
- Classification and Regression Trees
- Neural Networks and Deep Learning
- Cluster Analysis
- Principal Components Analysis
- Market Basket Analysis, Recommendation Engines, and Sequential Analysis
- Creating Ensembles and Multiclass Classification
- Time Series and Causality
- Text Mining
- R on the Cloud
- R Fundamentals
- Sources
Download Free PDF / Read Online
Author(s): Sibanjan Das, Umit Mert Cakmak
Publisher: Packt Publishing
Published: April 2017
Format(s): Online
File size: –
Number of pages: 420
Download / View Link(s): This offer has ended.
Free as of 02/16/2020.
Publisher: Packt Publishing
Published: April 2017
Format(s): Online
File size: –
Number of pages: 420
Download / View Link(s): This offer has ended.
Free as of 02/16/2020.