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R for Data Science: Implementing Machine Learning Models

R for Data Science: Implementing Machine Learning Models

Paperback

General Computers

ISBN10: 6209540546
ISBN13: 9786209540547
Publisher: LAP Lambert Academic Publishing
Published: Feb 16 2026
Pages: 164
Weight: 0.50
Height: 0.38 Width: 6.00 Depth: 9.00
Language: English
Unlock the power of machine learning in R with R for Data Science: Implementing Machine Learning Models. This comprehensive guide equips data scientists, analysts, and R enthusiasts with the practical skills needed to build, evaluate, and deploy advanced machine learning solutions across domains. Covering both fundamental and advanced topics, this book blends theory, hands-on examples, and real-world workflows to empower readers to harness R's full capabilities.Learn how to: - Preprocess, clean, and transform data for robust analysis.- Build predictive models with regression, classification, and time series techniques.- Apply natural language processing and text analytics to extract insights from unstructured data.- Explore clustering, dimensionality reduction, and anomaly detection in unsupervised learning.- Optimize models through hyperparameter tuning, ensemble methods, and stacking strategies.- Develop reproducible workflows, pipelines, and deployment-ready solutions in R.

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