Data Science Interview: Prep for SQL, Panda, Python, R Language, Machine Learning, DBMS and RDBMS - And More - The Full , (Paperback)

Are YOU looking for a data scientist job?

Then keep reading...

The median annual salary for a Data Scientist is $98,230, according to the Bureau of Labor Statistics.

Data science job postings grew by 31% over the past few years, while data science job searches only rose by 14% over the same period. This high demand has led to a shortage of over 150,000 data science professionals.

Glassdoor ranks data science, as the #2 job in America for 2022, and this trend is likely to continue.

Data science is one of the most in-demand professions today. It's also one of the highest paid and offers great benefits. It's also one of the hardest to get into, with only 1 in every 10 applicants being accepted by top companies like Google and Facebook. And as such, there are many challenges that come with this profession such as finding your dream job, getting through interviews and landing the offer letter.

You don't have to be intimidated by interviews anymore! With this Data Science Interview book, you'll be prepared for questions compiled from real data scientists who work at top companies including Google, Facebook, and Amazon & NASA.

You can use this Data Science Interview book as an effective study guide before going into any interview or even just brush up on some concepts if you feel confident about them already. Either way it'll be worth it because we know how difficult it is to find good jobs in today's market! Don't let another opportunity pass you by - buy this book now and start preparing for your next big data science interview!

CONTENTS:

1. INTRODUCTION

Meaning of Data Science

Background Interview Questions and Solutions

Careers in Data Science

1. CHAPTER 1: MASTERING THE BASICS

Statistics

Probability

Linear Algebra

1. CHAPTER 2: PYTHON
2. CHAPTER 3: PANDA

Numpy Interview Questions

1. CHAPTER 4: MACHINE LEARNING

PCA Interview Questions

Curse of Dimensionality

Support Vector Machine (SVM)

Overfitting and Underfitting

1. CHAPTER 5: R LANGUAGE
2. CSV files in R Programming

Confusion Matrix

Random Forest in R

1. K-MEANS Clustering
2. CHAPTER 6: SQL
3. DBMS and RDBMS
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