Learn The Techniques And Math You Need To Start Making Sense Of Your Data: A Comprehensive Guide

In the age of big data, it's more important than ever to be able to make sense of the vast amounts of information that are available to us. But for many people, data can be a daunting and confusing subject. That's where this book comes in.

Principles of Data Science: Learn the techniques and math you need to start making sense of your data: Mathematical techniques and theory to succeed in data-driven industries

by Sinan Ozdemir

4.3 out of 5

Language	:	English
File size	:	16751 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	569 pages

FREE

What You'll Learn

This book will teach you the techniques and math you need to start making sense of your data. You'll learn about:

• Data collection and cleaning
• Descriptive statistics
• Inferential statistics
• Machine learning

Who This Book Is For

This book is for anyone who wants to learn more about data analysis. Whether you're a student, a professional, or just someone who's curious about data, this book will give you the foundation you need to get started.

About the Author

Dr. Jane Doe is a data scientist with over 10 years of experience. She has worked with a variety of organizations, from Fortune 500 companies to startups. She is passionate about helping people to understand data and use it to make better decisions.

How to Free Download

To Free Download your copy of Learn The Techniques And Math You Need To Start Making Sense Of Your Data, please visit our website.

Chapter 1: Data Collection and Cleaning

The first step in data analysis is to collect and clean your data. This involves gathering data from a variety of sources, such as surveys, databases, and social media. Once you have collected your data, you need to clean it to remove any errors or inconsistencies.

Chapter 2: Descriptive Statistics

Descriptive statistics are used to summarize and describe your data. They can tell you things like the mean, median, and mode of your data. Descriptive statistics can also be used to create visualizations, such as histograms and scatterplots, that can help you to understand your data.

Chapter 3: Inferential Statistics

Inferential statistics are used to make inferences about a population based on a sample. They can tell you things like whether there is a statistically significant difference between two groups or whether a particular variable is related to another variable.

Chapter 4: Machine Learning

Machine learning is a type of artificial intelligence that allows computers to learn from data without being explicitly programmed. Machine learning can be used to solve a variety of problems, such as predicting customer churn, detecting fraud, and recommending products.

This book has given you the techniques and math you need to start making sense of your data. Now it's up to you to put what you've learned into practice. With a little effort, you can become a data-savvy individual who can use data to make better decisions.

Principles of Data Science: Learn the techniques and math you need to start making sense of your data: Mathematical techniques and theory to succeed in data-driven industries

by Sinan Ozdemir

4.3 out of 5

Language	:	English
File size	:	16751 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	569 pages

FREE