Get answers to frequently asked questions on Data Science and Machine Learning using R

Key Features

Understand the capabilities of the R programming language

Most of the machine learning algorithms and their R implementation covered in depth

Answers on conceptual data science concepts are also covered

Description
This book prepares you for the Data Scientist and Machine Learning Engineer interview w.r.t. R programming language.
The book is divided into various parts, making it easy for you to remember and associate with the questions asked in an interview. It covers multiple possible transformations and data filtering techniques in depth. You will be able to create visualizations like graphs and charts using your data. You will also see some examples of how to build complex charts with this data. This book covers the frequently asked interview questions and shares insights on the kind of answers that will help you get this job.
By the end of this book, you will not only crack the interview but will also have a solid command of the concepts of Data Science as well as R programming.

What will you learn

Get answers to the basics, intermediate and advanced questions on R programming

Understand the transformation and filtering capabilities of R

Know how to perform visualization using R

Who this book is for
This book is a must for anyone interested in Data Science and Machine Learning. Anyone who wants to clear the interview can use it as a last-minute revision guide.

Table of Contents
1. Data Science basic questions and terms
2. R programming questions
3. GGPLOT Questions
4. Statistics with excel sheet

About the Author
Vishwanathan Narayanan has 18 years of experience in the field of information technology and data analysis. He made many enterprise-level applications with stable output and scalability. Advanced level data analysis for complex problems using both R and Python has been the key area of work for many years. Extreme programmer on Java, Python, R, and many more technologies

 

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Spis treści

Data Science and Machine Learning Interview Questions Using R eBook -- spis treści