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Hands-On Data Analysis with Scala

Hands-On Data Analysis with Scala: Perform data collection, processing, manipulation, and visualization with Scala

By Rajesh Gupta
$35.99 $24.99
Book May 2019 298 pages 1st Edition
eBook
$35.99 $24.99
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eBook
$35.99 $24.99
Print
$48.99
Subscription
$15.99 Monthly

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Product Details

Publication date : May 3, 2019
Length 298 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781789346114
Category :
Data
Languages :
Scala (Expert)
Concepts :
Data Analysis
toc View table of contents toc Preview Book toc Download Code

Key benefits

  • A beginner's guide for performing data analysis loaded with numerous rich, practical examples
  • Access to popular Scala libraries such as Breeze, Saddle for efficient data manipulation and exploratory analysis
  • Develop applications in Scala for real-time analysis and machine learning in Apache Spark

Description

Efficient business decisions with an accurate sense of business data helps in delivering better performance across products and services. This book helps you to leverage the popular Scala libraries and tools for performing core data analysis tasks with ease. The book begins with a quick overview of the building blocks of a standard data analysis process. You will learn to perform basic tasks like Extraction, Staging, Validation, Cleaning, and Shaping of datasets. You will later deep dive into the data exploration and visualization areas of the data analysis life cycle. You will make use of popular Scala libraries like Saddle, Breeze, Vegas, and PredictionIO for processing your datasets. You will learn statistical methods for deriving meaningful insights from data. You will also learn to create applications for Apache Spark 2.x on complex data analysis, in real-time. You will discover traditional machine learning techniques for doing data analysis. Furthermore, you will also be introduced to neural networks and deep learning from a data analysis standpoint. By the end of this book, you will be capable of handling large sets of structured and unstructured data, perform exploratory analysis, and building efficient Scala applications for discovering and delivering insights

What you will learn

Techniques to determine the validity and confidence level of data Apply quartiles and n-tiles to datasets to see how data is distributed into many buckets Create data pipelines that combine multiple data lifecycle steps Use built-in features to gain a deeper understanding of the data Apply Lasso regression analysis method to your data Compare Apache Spark API with traditional Apache Spark data analysis

What do you get with eBook?

Feature icon Instant access to your Digital eBook purchase
Feature icon Download this book in EPUB and PDF formats
Feature icon Access this title in our online reader with advanced features
Feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details

Publication date : May 3, 2019
Length 298 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781789346114
Category :
Data
Languages :
Scala (Expert)
Concepts :
Data Analysis

Table of Contents

14 Chapters
Preface Packt Packt
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Section 1: Scala and Data Analysis Life Cycle Packt Packt
Section 1: Scala and Data Analysis Life Cycle
Scala Overview Packt Packt
Scala Overview
Getting started with Scala
Overview of object-oriented and functional programming
Scala case classes and the collection API
Overview of Scala libraries for data analysis
Summary
Data Analysis Life Cycle Packt Packt
Data Analysis Life Cycle
Data journey
Sourcing data
Understanding data
Using ML to learn from data
Creating a data pipeline
Summary
Data Ingestion Packt Packt
Data Ingestion
Data extraction
Data staging
Cleaning and normalizing
Enriching
Organizing and storing
Summary
Data Exploration and Visualization Packt Packt
Data Exploration and Visualization
Sampling data
Performing ad hoc analysis
Finding a relationship between data elements
Visualizing data
Summary
Applying Statistics and Hypothesis Testing Packt Packt
Applying Statistics and Hypothesis Testing
Basics of statistics
Vector level statistics
Random data generation
Hypothesis testing
Summary
Section 2: Advanced Data Analysis and Machine Learning Packt Packt
Section 2: Advanced Data Analysis and Machine Learning
Introduction to Spark for Distributed Data Analysis Packt Packt
Introduction to Spark for Distributed Data Analysis
Spark setup and overview
Spark Datasets and DataFrames
Sourcing data using Spark
Using Spark to explore data
Summary
Traditional Machine Learning for Data Analysis Packt Packt
Traditional Machine Learning for Data Analysis
ML overview
Decision trees
Random forest
Ridge and lasso regression
k-means cluster analysis
Natural language processing for data analysis
Algorithm selections
Summary
Section 3: Real-Time Data Analysis and Scalability Packt Packt
Section 3: Real-Time Data Analysis and Scalability
Near Real-Time Data Analysis Using Streaming Packt Packt
Near Real-Time Data Analysis Using Streaming
Overview of streaming
Spark Streaming overview
Streaming a k-means clustering algorithm using Spark
Streaming linear regression using Spark
Summary
Working with Data at Scale Packt Packt
Working with Data at Scale
Working with data at scale
Cost considerations
Reliability considerations
Summary
Another Book You May Enjoy Packt Packt
Another Book You May Enjoy
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Authors (1)

Profile Rajesh Gupta
Linkedin
Rajesh is a Hands-on Big Data Tech Lead and Enterprise Architect with extensive experience in the full life cycle of software development. He has successfully architected, developed and deployed highly scalable data solutions using Spark, Scala and Hadoop technology stack for several enterprises. A passionate, hands-on technologist, Rajesh has masters degrees in Mathematics and Computer Science from BITS, Pilani (India).
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