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The Statistics and Calculus with Python Workshop

The Statistics and Calculus with Python Workshop

By : Peter Farrell , Alvaro Fuentes , Ajinkya Sudhir Kolhe, Quan Nguyen , Alexander Joseph Sarver , Marios Tsatsos
4.7 (10)
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The Statistics and Calculus with Python Workshop

The Statistics and Calculus with Python Workshop

4.7 (10)
By: Peter Farrell , Alvaro Fuentes , Ajinkya Sudhir Kolhe, Quan Nguyen , Alexander Joseph Sarver , Marios Tsatsos

Overview of this book

Are you looking to start developing artificial intelligence applications? Do you need a refresher on key mathematical concepts? Full of engaging practical exercises, The Statistics and Calculus with Python Workshop will show you how to apply your understanding of advanced mathematics in the context of Python. The book begins by giving you a high-level overview of the libraries you'll use while performing statistics with Python. As you progress, you'll perform various mathematical tasks using the Python programming language, such as solving algebraic functions with Python starting with basic functions, and then working through transformations and solving equations. Later chapters in the book will cover statistics and calculus concepts and how to use them to solve problems and gain useful insights. Finally, you'll study differential equations with an emphasis on numerical methods and learn about algorithms that directly calculate values of functions. By the end of this book, you’ll have learned how to apply essential statistics and calculus concepts to develop robust Python applications that solve business challenges.
Table of Contents (14 chapters)
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Preface

Data Preparation

All applied statistics starts with a dataset and a problem to solve. In the real world, we never do statistical analysis in a vacuum; there is always a business problem to solve, a topic that needs to be quantitatively understood, or a scientific question to ask. Understanding the problem is always the very first step of any statistical analysis. The second step is to collect and prepare the data. Data collection is not a topic of this book, so we will go directly into data preparation. Therefore, before diving into doing some statistical calculations, we need to make sure we understand our business problem and that we have prepared our dataset.

Introducing the Dataset

In this subsection, we will introduce the dataset we will use in this chapter and perform some basic data preparation tasks. Knowing the dataset will give you a bit more context when we define the business problem.

We are going to use the strategy games dataset, which contains real-world information...

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