February 2016
Beginner to intermediate
312 pages
7h 23m
English
Overview
Dive into the world of regression analysis guided by Python in this comprehensive book. From simple linear regression to complex models, you'll gain a deep understanding of how to analyze data and predict outcomes. By the end of this book, you will be equipped with the skills to tidy data, build models, and apply regression techniques to real-world problems.
What this Book will help me do
- Understand and format datasets to prepare them for regression analysis efficiently.
- Build and implement various regression models, such as linear and logistic regression, to solve data science problems.
- Develop techniques to combat overfitting and ensure predictive accuracy.
- Learn to scale and adapt regression models to large datasets and apply incremental learning.
- Apply the skills gained to make informed business decisions using predictive insights from regression models.
Author(s)
Luca Massaron and Alberto Boschetti are seasoned data professionals with years of expertise in data science, regression analysis, and Python programming. They are passionate about teaching and have crafted this book to demystify regression for learners interested in predictive analytics. Their approachable style ensures concepts are accessible yet comprehensive.
Who is it for?
This book is ideal for Python developers and data scientists who have a foundational knowledge of math and statistics. Whether you're looking to delve deeper into predictive modeling or efficiently analyze datasets, this book provides step-by-step guidance. If you've dabbled in data science and wish to expand your skillset to include regression analysis, this book is for you!
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