Large Scale Machine Learning with Spark - Couverture souple

Karim, Md. Rezaul; Kaysar, Md. Mahedi

Couverture souple

ISBN 10 : 1785888749 ISBN 13 : 9781785888748

Editeur : Packt Publishing, 2016

A propos du livre

Biographie de l'auteur :

Md. Rezaul Karim is a software developer and researcher currently working at the Insight Centre for Data Analytics, Ireland (the largest data analytics center across the Ireland and the largest semantic web research institute in the world) as a PhD Researcher. He is a PhD candidate at the National University of Ireland, Galway. He also holds an ME (Master of Engineering in Computer Engineering) from the Kyung Hee University, Korea, majoring data mining and knowledge discovery. He also has a BSc (Bachelor of Science, in Computer Science, University of Dhaka, Bangladesh) degree.

He has more than 8 years of experience in the area of research and development with a strong knowledge of algorithms and data structures concentrating C, C++, Java, R, Python, Julia and Big Data technologies (Apache Spark/Hadoop/MapReduce). Before joining the Insight Centre for Data Analytics, he had been working as a Lead Software Engineer with Samsung Electronics, where he worked with the distributed Samsung R&D centers across the world including Korea, India, Vietnam, Turkey, UAE, Brazil, and Bangladesh.

Even before this, he worked as a Graduate Research Assistant in the Database Lab, Kyung Hee University, Korea, as an R&D Engineer with BMTech21 Worldwide, Korea, and as a Software Engineer with i2SoftTechnology, Dhaka, Bangladesh.

He has published more than 30 research papers in renowned peer-reviewed international journals and conferences focusing the area of data mining, big data, and bioinformatics with good citations.

Md. Mahedi Kaysar is a Software Engineer and Researcher at Insight Centre for Data Analytics, National University of Ireland [NUIG] (the largest data analytics center across the Ireland and the largest semantic web research institute in the world). He has more than 4 years of experience in research and development with strong knowledge of algorithms and data structures concentrating Java and Scala. He obtained his BSc in Computer Science and Engineering from Chittagong University of Engineering & Technology, Bangladesh. Previously, he worked with Samsung Electronics as a Software Engineer where he was involved in several commercialization projects.

His research interests include Semantic Web, Linked Data, Big Data, Internet of Everything, and Machine Learning. He is involved in a research project in collaboration with CISCO Systems Inc. in the area of Internet of Everything and Semantic Web Technologies. His duties are to develop an IoT-enabled meeting management system, stream processing, integrating the different technological components, and showcasing the use cases of the project.

Présentation de l'éditeur :

Key Features

• Get the most up-to-date book on the market that focuses on design, engineering, and scalable solutions in machine learning with Spark 2
• We use Spark's machine learning library in a big data environment
• You will learn to develop high-value applications at scale with ease and a personalized design

Book Description

Scaling out and deploying algorithms, interactions, and clustering are crucial steps in the process of optimizing any application. By maintaining and streaming data, Spark can figure out when to cache data in-memory, 100x faster than Hadoop and Mahoot. This means data streaming and analytics can run and complete jobs a lot quicker, making Spark ideal for large data-intensive applications.

This book focuses on design, engineering, and scalable solutions in machine learning with Spark. You will learn how to install Spark with all new features as in the latest version Spark 2. You will also get to grips with Spark MLlib and Spark ML and its implementation for machine learning algorithms. Moving ahead, we'll explore about important concepts such as Dataframes and advanced feature engineering. After studying more about the development and deployment of an application, you will also find out about the other external libraries available for your data analysis.

What you will learn

• Solid theoretical understanding about machine learning algorithms and techniques for new and unknown datasets
• Set up and configure Spark, and develop your first Spark application using Scala, Java, and SparkR
• Use ML and MLlib implement practical and large-scale machine learning pipelines and applications including collaborative filtering, classification, regression, clustering, association rule mining, twitter sentiment analysis, and dimensionality reduction
• Scale up your machine learning application on large cluster or even cloud computing environment like Amazon EC2
• Enhance performance of your machine learning models
• Tune your machine learning models for cross-validation, grid searching, hyperparameter tuning and train validation split
• Deal with large-scale text data, including feature extraction and using text data as input to machine learning models
• Develop machine learning application real-time streaming data using Spark Streaming

À propos de cette édition

• Éditeur: Packt Publishing
• Date d'édition: 2016
• ISBN 10: 1785888749
• ISBN 13: 9781785888748
• Reliure: Broché
• Nombre de pages: 476