Items related to Large Scale Machine Learning with Spark

Large Scale Machine Learning with Spark - Softcover

 
9781785888748: Large Scale Machine Learning with Spark
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Discover everything you need to build robust machine learning applications with Spark 2.0

About This Book

  • Get the most up-to-date book on the market that focuses on design, engineering, and scalable solutions in machine learning with Spark 2.0.0
  • Use Spark’s machine learning library in a big data environment
  • You will learn how to develop high-value applications at scale with ease and a develop a personalized design

Who This Book Is For

This book is for data science engineers and scientists who work with large and complex data sets. You should be familiar with the basics of machine learning concepts, statistics, and computational mathematics. Knowledge of Scala and Java is advisable.

What You Will Learn

  • Get solid theoretical understandings of ML algorithms
  • Configure Spark on cluster and cloud infrastructure to develop applications using Scala, Java, Python, and R
  • Scale up ML applications on large cluster or cloud infrastructures
  • Use Spark ML and MLlib to develop ML pipelines with recommendation system, classification, regression, clustering, sentiment analysis, and dimensionality reduction
  • Handle large texts for developing ML applications with strong focus on feature engineering
  • Use Spark Streaming to develop ML applications for real-time streaming
  • Tune ML models with cross-validation, hyperparameters tuning and train split
  • Enhance ML models to make them adaptable for new data in dynamic and incremental environments

In Detail

Data processing, implementing related algorithms, tuning, scaling up and finally deploying are some crucial steps in the process of optimising any application.

Spark is capable of handling large-scale batch and streaming data to figure out when to cache data in memory and processing them up to 100 times faster than Hadoop-based MapReduce. This means predictive analytics can be applied to streaming and batch to develop complete machine learning (ML) applications a lot quicker, making Spark an ideal candidate for large data-intensive applications.

This book focuses on design engineering and scalable solutions using ML with Spark. First, you will learn how to install Spark with all new features from the latest Spark 2.0 release. Moving on, you’ll explore important concepts such as advanced feature engineering with RDD and Datasets. After studying developing and deploying applications, you will see how to use external libraries with Spark.

In summary, you will be able to develop complete and personalised ML applications from data collections,model building, tuning, and scaling up to deploying on a cluster or the cloud.

Style and approach

This book takes a practical approach where all the topics explained are demonstrated with the help of real-world use cases.

"synopsis" may belong to another edition of this title.

About the Author:

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.

"About this title" may belong to another edition of this title.

  • PublisherPackt Publishing
  • Publication date2016
  • ISBN 10 1785888749
  • ISBN 13 9781785888748
  • BindingPaperback
  • Number of pages476

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