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Training Systems Using Python Statistical Modeling

You're reading from Training Systems Using Python Statistical Modeling Explore popular techniques for modeling your data in Python

Product type Paperback

Published in May 2019

Publisher Packt

ISBN-13 9781838823733

Length 290 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Machine Learning

Author (1):

Curtis Miller

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Table of Contents (9) Chapters

Preface

1. Classical Statistical Analysis FREE CHAPTER

2. Introduction to Supervised Learning

3. Binary Prediction Models

4. Regression Analysis and How to Use It

5. Neural Networks

6. Clustering Techniques

7. Dimensionality Reduction

8. Other Books You May Enjoy

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Who this book is for

If you are a statistician or a data analyst and want to learn how to build statistical modeling systems using Python tools and packages, then this is the perfect book for you. You will dive into various different aspects of statistical modeling and training, and will learn how to employ those concepts using the Python programming language.

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Authors (1)

Curtis Miller

Curtis Miller

Curtis Miller is a doctoral candidate at the University of Utah studying mathematical statistics. He writes software for both research and personal interest, including the R package (CPAT) available on the Comprehensive R Archive Network (CRAN). Among Curtis Miller's publications are academic papers along with books and video courses all published by Packt Publishing. Curtis Miller's video courses include Unpacking NumPy and Pandas, Data Acquisition and Manipulation with Python, Training Your Systems with Python Statistical Modelling, and Applications of Statistical Learning with Python. His books include Hands-On Data Analysis with NumPy and Pandas.

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