Data Science Foundations and Machine Learning with R: From Data to Decisions
Welcome
Welcome to the online companion to Data Science Foundations and Machine Learning with R: From Data to Decisions. This platform supports your learning journey with hands-on code, datasets, and resources designed to reinforce key ideas from the book.
Whether you are a student, professional, or independent learner, this book offers a practical and accessible path into data science and machine learning, emphasizing application over abstract theory. No prior programming or analytics experience is required; only curiosity and a willingness to explore.
Built around the Data Science Workflow, the book guides you through data wrangling, exploratory analysis, modeling, evaluation, and deployment. A dedicated chapter introduces R from scratch, ensuring a smooth start for beginners. Using R, an open-source language widely used in both academia and industry, you will gain hands-on experience with:
- Data cleaning and transformation;
- Visual exploration and statistical summaries;
- Supervised learning techniques including decision trees, regression, k-nearest neighbors, naΓ―ve Bayes, and neural networks;
- Unsupervised learning with clustering;
- Model evaluation and comparison.
The book also includes the liver package, available on CRAN, which provides curated datasets and helper functions to support interactive learning.
You can always access the latest version of the book at
π https://book-data-science-r.netlify.app
and explore the source code or contribute via GitHub:
π https://github.com/RezaMoammadi/Book-Data-Science-R
Work in Progress
This is a living resource and your feedback helps improve it. If you have suggestions, corrections, or ideas:
Thank you for being part of this learning journey!
Book by Reza Mohammadi is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
The book website is hosted on Netlify.
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