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Declaring the Objectives

This chapter introduces and explains (yet again, from a developer's perspective) the basic objectives behind statistics for data science and introduces the reader to the important terms and key concepts (with explanations and examples) that are used throughout the book.

In this chapter, we've broken things down into the following topics:

A primer on the key objectives of data science
Bringing statistics into data science
Common terminologies used with statistics and data science

Key benefits

No need to take a degree in statistics, read this book and get a strong statistics base for data science and real-world programs;

Implement statistics in data science tasks such as data cleaning, mining, and analysis

Learn all about probability, statistics, numerical computations, and more with the help of R programs

Description

Data science is an ever-evolving field, which is growing in popularity at an exponential rate. Data science includes techniques and theories extracted from the fields of statistics; computer science, and, most importantly, machine learning, databases, data visualization, and so on. This book takes you through an entire journey of statistics, from knowing very little to becoming comfortable in using various statistical methods for data science tasks. It starts off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for statistical computation are clearly explained along with logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks. By the end of the book, you will be comfortable with performing various statistical computations for data science programmatically.

What you will learn

• Analyze the transition from a data developer to a data scientist mindset

• Get acquainted with the R programs and the logic used for statistical computations

• Understand mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more

• Learn to implement statistics in data science tasks such as data cleaning, mining, and analysis

• Learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks

• Get comfortable with performing various statistical computations for data science programmatically

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Frequently bought together

Basic Statistics and Data Mining for Data Science

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Adi Mar 02, 2018

Statistics is the main concept in data science , this book helps in analyzing from data developer to a data scientist , R programming logic's for stats and many more concepts. Useful for anyone who is interested in data science

Amazon Verified review

Vivek V. Oct 06, 2018

Nice book

Deepak Singh Nov 10, 2019

Imprssive work

Alexander Jul 31, 2018

A lot of blank space on approx. 200pages thus covering topics superficially. I would not recommend this book except to those who are looking for a quick intro.

Chrisfs Jan 29, 2019

I am very disappointed by the book. The contents don't match the title at all. There is very little statistics in the book. It covers the basics of preparing data for analysis and covers the dictionary meaning of some machine learning and statistical terms but it doesn't explain anything in any sort of detail. If you buy this book to learn about statistics, then it's very disappointing and a complete waste of money

Statistics for Data Science: Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks

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Statistics for Data Science

Declaring the Objectives

Key objectives of data science

Summary

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What you will learn

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Statistics for Data Science: Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks

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Key benefits

Description

Who is this book for?

What you will learn

Product Details

What do you get with Print?

Contact Details

Shipping Address

Billing Address

Product Details

Packt Subscriptions

Frequently bought together

Table of Contents

Recommendations for you

Customer reviews

People who bought this also bought

About the author

FAQs