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Cracking the Data Science Interview

You're reading from Cracking the Data Science Interview Unlock insider tips from industry experts to master the data science field

Product type Paperback

Published in Feb 2024

Publisher Packt

ISBN-13 9781805120506

Length 404 pages

Edition 1st Edition

Languages

Python

Tools

Git

Concepts

Data Science

Authors (2):

Leondra R. Gonzalez

Aaren Stubberfield

View More author details

Table of Contents (21) Chapters

Preface

1. Part 1: Breaking into the Data Science Field FREE CHAPTER

2. Chapter 1: Exploring Today’s Modern Data Science Landscape

3. Chapter 2: Finding a Job in Data Science

4. Part 2: Manipulating and Managing Data

5. Chapter 3: Programming with Python

6. Chapter 4: Visualizing Data and Data Storytelling

7. Chapter 5: Querying Databases with SQL

8. Chapter 6: Scripting with Shell and Bash Commands in Linux

9. Chapter 7: Using Git for Version Control

10. Part 3: Exploring Artificial Intelligence

11. Chapter 8: Mining Data with Probability and Statistics

12. Chapter 9: Understanding Feature Engineering and Preparing Data for Modeling

13. Chapter 10: Mastering Machine Learning Concepts

14. Chapter 11: Building Networks with Deep Learning

15. Chapter 12: Implementing Machine Learning Solutions with MLOps

16. Part 4: Getting the Job

17. Chapter 13: Mastering the Interview Rounds

18. Chapter 14: Negotiating Compensation

19. Index

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20. Other Books You May Enjoy

Introducing populations and samples

Statistics is the art of extracting meaningful insights from data, and it all begins with a thorough understanding of populations and samples. In this section, we will explore the fundamental concepts that underpin statistical analysis by distinguishing between populations and samples.

Understanding these concepts is important because they form the basis for generalizing observations from a subset of data to a larger group. By investigating the intricacies of populations and samples, you will gain the necessary tools to make sound inferences and draw reliable conclusions from the data you encounter. So, let‘s embark on this enlightening journey and uncover the foundations of statistical analysis.

Defining populations and samples

In the realm of statistics, a population refers to the entire group of individuals, objects, or events that we are interested in studying. For instance, if we wanted to research the average height of all adults...

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Authors (2)

Leondra R. Gonzalez

Leondra R. Gonzalez

Leondra R. Gonzalez is a data scientist at Microsoft and Chief Data Officer for tech startup CulTRUE, with 10 years of experience in tech, entertainment, and advertising. During her academic career, she has completed educational opportunities with Google, Amazon, NBC, and AT&T.

See other products by Leondra R. Gonzalez

Stubberfield

Stubberfield

Aaren Stubberfield is a senior data scientist for Microsoft's digital advertising business and the author of three popular courses on Datacamp. He graduated with an MS in Predictive Analytics and has over 10 years of experience in various data science and analytical roles focused on finding insights for business-related questions.

See other products by Stubberfield

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