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Principles of Data Science

You're reading from Principles of Data Science Understand, analyze, and predict data using Machine Learning concepts and tools

Product type Paperback

Published in Dec 2018

Publisher Packt

ISBN-13 9781789804546

Length 424 pages

Edition 2nd Edition

Languages

Python

Tools

NumPy

Concepts

Data Science

Authors (3):

Sunil Kakade

Sinan Ozdemir

Marco Tibaldeschi

View More author details

Table of Contents (17) Chapters

Preface

1. How to Sound Like a Data Scientist FREE CHAPTER

2. Types of Data

3. The Five Steps of Data Science

4. Basic Mathematics

5. Impossible or Improbable - A Gentle Introduction to Probability

6. Advanced Probability

7. Basic Statistics

8. Advanced Statistics

9. Communicating Data

10. How to Tell If Your Toaster Is Learning – Machine Learning Essentials

11. Predictions Don't Grow on Trees - or Do They?

12. Beyond the Essentials

13. Case Studies

14. Building Machine Learning Models with Azure Databricks and Azure Machine Learning service

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Index

Preface

The topic of this book is data science, which is a field of study that has been growing rapidly for the past few decades. Today, more companies than ever before are investing in big data and data science to improve business performance, drive innovation, and create new revenue streams by building data products. According to LinkedIn's 2017 US Emerging Jobs Report, machine learning engineer, data scientist, and big data engineer rank among the top emerging jobs, and companies in a wide range of industries are seeking people with the requisite skills for those roles.

We will dive into topics from all three areas and solve complex problems. We will clean, explore, and analyze data in order to derive scientific and accurate conclusions. Machine learning and deep learning techniques will be applied to solve complex data tasks.

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Authors (3)

Sinan Ozdemir

Sinan Ozdemir

Sinan is an active lecturer focusing on large language models and a former lecturer of data science at the Johns Hopkins University. He is the author of multiple textbooks on data science and machine learning including "Quick Start Guide to LLMs". Sinan is currently the founder of LoopGenius which uses AI to help people and businesses boost their sales and was previously the founder of the acquired Kylie.ai, an enterprise-grade conversational AI platform with RPA capabilities. He holds a Master's Degree in Pure Mathematics from Johns Hopkins University and is based in San Francisco.

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Tibaldeschi

Tibaldeschi

Marco Tibaldeschi, born in 1983, Master's degree in informatic engineering, has actively worked on the web since 1994. Thanks to the fact that he is the fourth of four brothers, he has always had a foot in the future. In 1998 he registered his fist domain which was one of the fist virtual web communities in Italy. Because of this, he has been interviewed by different national newspapers and radio stations, and a research book has been written by University of Pisa in order to understand the social phenomenon. In 2003, he founded DBN Communication, a web consulting company that owns and develops eDock, a SaaS that helps sellers to manage their inventories and orders on the biggest marketplaces in the world (like Amazon and eBay).

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Kakade

Kakade

Sunil Kakade is a technologist, educator, and senior leader with expertise in creating data and AI-driven organizations. He is in the adjunct faculty at Northwestern University, Evanston, IL, where he teaches graduate courses of data science and big data. He has several research papers to his credit and has presented his work in big data applications at reputable conferences. He has US patents in areas of big data and retail processes. He is passionate about applying data science to improve business outcomes and save patients' lives. At present, Sunil leads the information architecture and analytics team for a large healthcare organization focused on improving healthcare outcomes and lives with his wife, Pratibha, and daughter, Preeti, in Scottsdale, Arizona.

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