Call Number: QA279 F219l 2021
Located: MainLB, New Acquisition(2nd Fl)
http://opac.nu.ac.th/vufind/Record/1027720
Features:
- Python is a powerful, open source programming language increasingly being used in data science, machine learning and computer science. Python and R are similar, but R was designed for statistics, while Python is multi-talented.
- This version replaces R with Python to make it accessible to a greater number of users outside of statistics, including those from Machine Learning.
- A reader coming to this book from an ML background will learn new statistical perspectives on learning from data.
- Topics include Model Selection, Shrinkage, Experiments with Blocks and Missing Data.
- Includes an Appendix on Python for beginners.
Linear Models with Python explains how to use linear models in physical science, engineering, social science and business applications. It is ideal as a textbook for linear models or linear regression courses.
Table of Contents
1.Introduction
2.Estimation
3.Inference
4.Prediction
5.Explanation
6.Diagnostics
7.Problems with the Predictors 8.Problems with the Errors
9.Transformation10.Model Selection
11.Shrinkage Methods
12.Insurance Redlining —A Complete Example
13.Missing Data
14.Categorical Predictors
15.One Factor Models
16.Models with Several Factors
17.Experiments with Blocks
18.About Python
