Machine Learning Mastery with R: From Linear Models to Deep Learning

By VEYTHORNE COMFORT

Machine Learning Mastery with R: From Linear Models to Deep Learning is a comprehensive, practice-oriented exploration of modern data science through the power of R. Designed for students, professionals, and researchers, this book bridges classical statistical thinking with the frontiers of artificial intelligence. It guides readers through every stage of the machine learning journey from data preprocessing and feature engineering to model optimization, deep learning, and ethical deployment.
Unlike many technical manuals that focus solely on algorithms, this book emphasizes conceptual clarity, interpretability, and responsible application. Each chapter integrates theory with practical implementation, using R's diverse ecosystem of packages such as tidymodels, caret, mlr3, keras, torch, and DALEX.
The author demonstrates how R's open-source nature fosters transparency, collaboration, and innovation in machine learning. Readers learn not only how to build models but why those models behave as they do developing both technical fluency and critical thinking.
Topics such as data bias, privacy, fairness, reproducibility, and explainable AI are woven throughout the text, ensuring that learners gain a complete understanding of the ethical and practical implications of machine learning. Whether working on academic research, industrial applications, or AI-driven startups, readers will find this book to be a definitive resource for mastering intelligent systems in R.
By the final chapter, readers emerge with a deep appreciation for R's versatility capable of building interpretable models, scalable pipelines, and powerful neural networks all within a reproducible and ethically grounded framework.
This book is not merely a technical reference; it is a roadmap for responsible mastery, empowering data scientists to create models that are both intelligent and humane.

• Format: Paperback
• Language: English
• ISBN: B0FWD68X8R
• ISBN13: 9798269975467
• Release Date: October 2025
• Publisher: Independently Published
• Length: 184 Pages
• Weight: 0.56 lbs.
• Dimensions: 0.4" x 6.0" x 9.0"