Data Science Handbook
eBook - ePub

Data Science Handbook

A Practical Approach

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Data Science Handbook

A Practical Approach

About this book

DATA SCIENCE HANDBOOK

This desk reference handbook gives a hands-on experience on various algorithms and popular techniques used in real-time in data science to all researchers working in various domains.

Data Science is one of the leading research-driven areas in the modern era. It is having a critical role in healthcare, engineering, education, mechatronics, and medical robotics. Building models and working with data is not value-neutral. We choose the problems with which we work, make assumptions in these models, and decide on metrics and algorithms for the problems. The data scientist identifies the problem which can be solved with data and expert tools of modeling and coding.

The book starts with introductory concepts in data science like data munging, data preparation, and transforming data. Chapter 2 discusses data visualization, drawing various plots and histograms. Chapter 3 covers mathematics and statistics for data science. Chapter 4 mainly focuses on machine learning algorithms in data science. Chapter 5 comprises of outlier analysis and DBSCAN algorithm. Chapter 6 focuses on clustering. Chapter 7 discusses network analysis. Chapter 8 mainly focuses on regression and naive-bayes classifier. Chapter 9 covers web-based data visualizations with Plotly. Chapter 10 discusses web scraping.

The book concludes with a section discussing 19 projects on various subjects in data science.

Audience

The handbook will be used by graduate students up to research scholars in computer science and electrical engineering as well as industry professionals in a range of industries such as healthcare.

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Yes, you can access Data Science Handbook by Kolla Bhanu Prakash in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Table of Contents
  3. Title Page
  4. Copyright
  5. Dedication
  6. Acknowledgment
  7. Preface
  8. 1 Data Munging Basics
  9. 2 Data Visualization
  10. 3 Basic Math and Statistics
  11. 4 Introduction to Machine Learning
  12. 5 Outlier Analysis
  13. 6 Cluster Analysis
  14. 7 Network Analysis with NetworkX
  15. 8 Basic Algorithmic Learning
  16. 9 Web-Based Data Visualizations with Plotly
  17. 10 Web Scraping with Beautiful Soup
  18. Data Science Projects
  19. End User License Agreement