Elements of Data Science, Machine Learning, and Artificial Intelligence Using R

Title:

Author:

Emmert-Streib, Frank. author.

ISBN:

9783031133398

Edition:

1st ed. 2023.

Physical Description:

XIX, 575 p. 162 illus., 156 illus. in color. online resource.

Contents:

Introduction -- Introduction to learning from data -- Part 1: General topics -- Prediction models -- Error measures -- Resampling -- Data types -- Part 2: Core methods -- Maximum Likelihood & Bayesian analysis -- Clustering -- Dimension Reduction -- Classification -- Hypothesis testing -- Linear Regression -- Model Selection -- Part 3: Advanced topics -- Regularization -- Deep neural networks -- Multiple hypothesis testing -- Survival analysis -- Generalization error -- Theoretical foundations -- Conclusion.

Subject Term:

Computational intelligence.

Artificial intelligence.

Telecommunication.

Machine learning.

Data mining.

Communications Engineering, Networks.

Data Mining and Knowledge Discovery.

Added Author:

Moutari, Salissou.

Dehmer, Matthias.

Added Corporate Author: