Free Principles of Data Science Book Available for Download - OpenStax
Principles of Data Science is intended to support one- or two-semester courses in data science. It is appropriate for data science majors and minors as well as students concentrating in business, finance, health care, engineering, the sciences, and a number of other fields where data science has become critically important.
Principles of Data Science PDF
An Introduction to Statistical Learning
What is statistical learning?
Regression
Classification
Resampling methods
Linear model selection and regularization
Moving beyond linearity
Tree-based methods
Support vector machines
Deep learning
Survival analysis
Unsupervised learning
Multiple testing
1 Preliminaries
2 Python Language Basics, IPython, and Jupyter Notebooks
3 Built-In Data Structures, Functions, and Files
4 NumPy Basics: Arrays and Vectorized Computation
5 Getting Started with pandas
6 Data Loading, Storage, and File Formats
7 Data Cleaning and Preparation
8 Data Wrangling: Join, Combine, and Reshape
9 Plotting and Visualization
10 Data Aggregation and Group Operations
11 Time Series
12 Introduction to Modeling Libraries in Python
13 Data Analysis Examples
AppendicesA Advanced NumPy
B More on the IPython System
Part I: An Introduction to Veridical Data Science1 An Introduction to Veridical Data Science
2 The Data Science Life Cycle
3 Setting Up Your Data Science Project
Part II: Preparing, Exploring, and Describing Data4 Data Preparation
5 Exploratory Data Analysis
6 Principal Component Analysis
7 Clustering
Part III: Prediction8 An Introduction to Prediction Problems
9 Continuous Responses and Least Squares
10 Extending the Least Squares Algorithm
11 Binary Responses and Logistic Regression
12 Decision Trees and the Random Forest Algorithm
13 Producing the Final Prediction Results
14 Conclusion
Answers to True or False Exercises
