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

Specificaties
Paperback, blz. | Engels
Springer International Publishing | e druk, 2024
ISBN13: 9783031133411
Rubricering
Springer International Publishing e druk, 2024 9783031133411
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

The textbook provides students with tools they need to analyze complex data using methods from data science, machine learning and artificial intelligence. The authors include both the presentation of methods along with applications using the programming language R, which is the gold standard for analyzing data. The authors cover all three main components of data science: computer science; mathematics and statistics; and domain knowledge. The book presents methods and implementations in R side-by-side, allowing the immediate practical application of the learning concepts. Furthermore, this teaches computational thinking in a natural way. The book includes exercises, case studies, Q&A and examples.

Specificaties

ISBN13:9783031133411
Taal:Engels
Bindwijze:paperback
Uitgever:Springer International Publishing

Inhoudsopgave

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.<p></p>

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