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Hands-On Data Analysis with Scala
Hands-On Data Analysis with Scala

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

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Hands-On Data Analysis with Scala

Section 1: Scala and Data Analysis Life Cycle

In this section, you will gain an insight into what data is, how it is prepared and processed, and how it is analyzed and stored. This section will also get you introduced to the Scala framework and how we use Scala with data. You will learn some basic commands in Scala. You will also understand what a data pipeline is and the tasks involved in this pipeline.

This section will contain the following chapters:

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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

Who is this book for?

If you are a data scientist or a data analyst who wants to learn how to perform data analysis using Scala, this book is for you. All you need is knowledge of the basic fundamentals of Scala programming.

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : May 03, 2019
Length: 298 pages
Edition : 1st
Language : English
ISBN-13 : 9781789346114
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Product Details

Publication date : May 03, 2019
Length: 298 pages
Edition : 1st
Language : English
ISBN-13 : 9781789346114
Category :
Languages :
Concepts :

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Table of Contents

13 Chapters
Section 1: Scala and Data Analysis Life Cycle Chevron down icon Chevron up icon
Scala Overview Chevron down icon Chevron up icon
Data Analysis Life Cycle Chevron down icon Chevron up icon
Data Ingestion Chevron down icon Chevron up icon
Data Exploration and Visualization Chevron down icon Chevron up icon
Applying Statistics and Hypothesis Testing Chevron down icon Chevron up icon
Section 2: Advanced Data Analysis and Machine Learning Chevron down icon Chevron up icon
Introduction to Spark for Distributed Data Analysis Chevron down icon Chevron up icon
Traditional Machine Learning for Data Analysis Chevron down icon Chevron up icon
Section 3: Real-Time Data Analysis and Scalability Chevron down icon Chevron up icon
Near Real-Time Data Analysis Using Streaming Chevron down icon Chevron up icon
Working with Data at Scale Chevron down icon Chevron up icon
Another Book You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(3 Ratings)
5 star 100%
4 star 0%
3 star 0%
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1 star 0%
M. Sharma Aug 14, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have been thinking about writing the review for this book for some time.I was planning to switch from R/SAS to Scala for data analysis and ML project on Spark.I was looking for a book which is quick read and cover various practical examples of using Scala with large datasets. Then I came across this book. It covers basics of language and shows how to use Scala/Spark for practical projects. It helped me to setup Scala and various tools and library on Spark cluster.Book is very methodical in its approach covering various aspects of big data analytics projects. It helped me to be productive in no time and start using Scala and Spark.One can finish this book in short period of time and will be ready to work on large scale Scala projects.Author has done great justice to the title and I highly recommend this work to anyone who wants to learn and adapt Scala/Spark.
Amazon Verified review Amazon
Sandy Jul 28, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great read, to quickly come up to speed on Data Analysis with Scala. The author explains everything in very simple terms and remove need of any prerequisites . It is must read for anybody interested on the subject. It doesn't waste anytime in theoretical concepts and jumps directly on the subject with step by step instructions with lot of examples. The contents and the style of book reflects author experience on the subject.
Amazon Verified review Amazon
bindu Jul 22, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very Resourceful book for learning Scala. Detailed explanation right from the setup. Each topic is well explained with UML diagrams followed by practical examples. This book even covers Spark and Machine Learning Core Concepts.
Amazon Verified review Amazon
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