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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Master scala’s advanced techniques to solve real-world problems in data analysis and gain valuable insights from your data
Key Features
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
Book DescriptionEfficient 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
Who this book is forIf 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.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Master scala’s advanced techniques to solve real-world problems in data analysis and gain valuable insights from your data
Key Features
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
Book DescriptionEfficient 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
Who this book is forIf 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.