Code repository for O'Reilly book
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AI-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
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Table of Content
- Exploratory Data Analysis
- Data and Sampling Distributions
- Statistical Experiments and Significance Testing
- Regression and Prediction
- Classification
- Statistical Machine Learning
- Unsupervised Learning
- Neural Networks
- Deep Learning
- Generative AI and Large Language Models (LLMs)
- Caveats and Concerns
Code Documentation
The R and Python source code from the book is available as browsable and searchable webpages containing all code, output, and figures from the book.
Download
Download the data and source code as ZIP archives:
- data.zip — the data files used throughout the book
- python.zip — the Python source code
- R.zip — the R source code
See also
Code repositories for first and second edition:
- First edition: https://github.com/andrewgbruce/statistics-for-data-scientists
- Second edition: https://github.com/gedeck/practical-statistics-for-data-scientists