Mastering Spark for Data Science
Placing the reader in the position of a commercial data scientist, this book covers the key attributes to solve real-world problems in areas such as music, financial markets, and global news. Introducing advanced techniques in Spark, it also comprehensively explores the surrounding eco-system with innovative and scalable solutions throughout
Offered by
Difficulty Level
Intermediate
Completion Time
18h40m
Language
English
About Book
Who Is This Book For?
This book is for those who have beginner-level familiarity with the Spark architecture and data science applications, especially those who are looking for a challenge and want to learn cutting edge techniques. This book assumes working knowledge of data science, common machine learning methods, and popular data science tools, and assumes you have previously run proof of concept studies and built prototypes.
Mastering Spark for Data Science
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 18h40m total length
The Big Data Science Ecosystem
Data Acquisition
Input Formats and Schema
Exploratory Data Analysis
Spark for Geographic Analysis
Scraping Link Based External Data
Building Communities
Building a Recommendation System
News Dictionary and Real Time Tagging System
Story Deduplication and Mutation
Anomaly Detection on Sentiment Analysis
TrendCalculus
Secure Data
Scalable Algorithms
Related Resources
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