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Data Science Workflow for Beginners

Start your Data Science Journey into a Successful High Paying Career

A.J. García

This book takes you on an exclusive tour of Data Science, discover the workflow successful data scientists are following and download 26 datasets to start your journey right away after following the 3 data visuzalization projects on the book.

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About

About

About the Book

This book brings to you a simple yet effective 40 to 60 mins introduction that will clear all your doubts about Data Sience and will answer some important questions like: What is data Science ? 

The book explores all the initial concepts a person might want to know about the data science workflow. There’s not coding, math or statistics required to successfully understand the goals and end results of this process. 

This book takes you on an exclusive tour of datasets and sites to download your first datasets. Then jumps into a comprehensive and  easy-to-follow data science process letting you go through 3 data visualization projects. (Python Code Understanding is Recommended for the Data Visualization projects)

  • 40 to 60 mins reading time.
  • 3 Data Visualization projects.
  • 10 Datasets sources.
  • 26 Quality datasets for your first visualizations.
  • Get the code and reuse in your own projects.

The ebook covers:

  • Intro to Data Science.
  • The Workflow of Data Science.
  • Data Science and Machine Learning.
  • Datasets to start right away.
  • Data Visualization Projects. (Python Code Understanding Recommended)

Check out other books from the author:

Javascript Snippets

Appwrite Up and Running

Front End Developer Interview Questions

ReactJS Documentation

Backend Developer Interview Questions

VueJS Documentation

React Redux Documentation

DevOPs

Data Science Workflow for Beginners

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Data ScienceBusiness AnalysisMachine Learning

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Author

About the Author

A.J. García

I started my coding career back in 2003. Lately I've been involved a lot in Javascript for frontend and the backend.

I would love passing along to you some of the experiences and challenges I've faced over the years.

Contents

Table of Contents

Introduction

  1. Who is this book for ?
  2. What this book covers ?

Chapter 1: Introduction to Data Science

  1. What is Data Science ?
  2. Who is a data scientist ?
  3. Structured Vs Unstructured data

Chapter 2: The Workflow of Data Science

Chapter 3: Data Science and Machine Learning

  1. What is Machine Learning ?
  2. Relation between Data Science and Machine Learning
  3. Machine learning model
  4. Supervised learning, unsupervised learning and deep learning
  5. Algorithms used in Machine Learning

Chapter 4: 26 Datasets to Build Successful Data Science Projects

  1. World Development Indicators
  2. Education Statistics
  3. World Bank Projects & Operations
  4. Airline Safety
  5. Weather in the US
  6. Adderall Drug Study
  7. Government Surveillance Planes Analysis
  8. Zika Virus Dataset
  9. FBI Firearm Background Check Data
  10. Political Ads on Facebook
  11. Hate News Story Dataset
  12. Voting Machines in 2016 Election
  13. n-grams from Google Books
  14. Common Crawl Corpus
  15. Landsat 8 Images
  16. Annual Survey of School System Finances
  17. World Bank Open Data
  18. International Monetary Fund Data
  19. Financial Times Market Data
  20. Google’s Open Images Dataset
  21. Stanford Dogs Dataset
  22. Indoor Scene Recognition Dataset
  23. Large Movie Review Dataset
  24. Berkeley DeepDrive Dataset
  25. Peking University/Baidu - Autonomous Driving
  26. Learning Analytics Data Set

Chapter 5: 10 Amazing sites with Free Datasets

Chapter 6: Data Visualization Projects

Keep exploring and learning about Data Science

Source Code Download

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