Editorial Reviews. About the Author. Patrick R. Nicolas. Patrick R. Nicolas is a lead R&D Due to its large file size, this book may take longer to download. Leverage Scala and Machine Learning to construct and study systems that can learn from data. Scala for Machine Learning Book Cover Print + eBook. Leverage Scala and Machine Learning to study and construct Scala for Machine Learning - Second Edition Book Cover Print + eBook.
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Leverage Scala and Machine Learning to construct and . Did you know that Packt offers eBook versions of every book published, with PDF. Scala Prog 09/04/ _Scala Machine Learn. eBook: Free eBooks Download. The post Scala Machine Learning Projects appeared first on WOW!. Scala for Machine Learning - Second Edition, published by Packt - PacktPublishing/Scala-for-Machine-Learning-Second-Edition. Clone or download.
Not in United Kingdom? Choose your country's store to see books available for purchase. See if you have enough points for this item. Sign in. Advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and Hadoop. Mastering Scala Machine Learning is intended for enthusiasts who want to plunge into the new pool of emerging techniques for machine learning. Some familiarity with standard statistical techniques is required.
Launching Xcode Launching Visual Studio Latest commit fdc1df7 Dec 17, About the Book The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Instructions and Navigation All chapter contains code files.
For breif instructions, visit authors GitHub repository by using the following link: The book uses the following libraries: Scala 2. You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Add files via upload. Sep 28, Code files. Title added to cart. Subscription About Subscription Pricing Login. Features Free Trial. Search for eBooks and Videos.
Scala for Machine Learning. Leverage Scala and Machine Learning to construct and study systems that can learn from data. Are you sure you want to claim this product using a token? Nicolas December Quick links: What do I get with a Packt subscription?
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Scala for Machine Learning - Second Edition -- Patrick R. Nicolas -ѕ©¶«ФД¶Б-ФЪПЯФД¶Б
Book Description The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Table of Contents. What You Will Learn Build dynamic workflows for scientific computing Leverage open source libraries to extract patterns from time series Write your own classification, clustering, or evolutionary algorithm Perform relative performance tuning and evaluation of Spark Master probabilistic models for sequential data Experiment with advanced techniques such as regularization and kernelization Solve big data problems with Scala parallel collections, Akka actors, and Apache Spark clusters Apply key learning strategies to a technical analysis of financial markets.
Authors Patrick R. Read More. Read More Reviews. Recommended for You. Python Machine Learning - Second Edition. Mastering Scala Machine Learning. Mastering Machine Learning with Spark 2. Building a Recommendation Engine with Scala. Scala for Data Science. All Rights Reserved. Contact Us.
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Scala for Machine Learning - Second Edition
Stay up to date with what's important in software engineering today. Become a contributor. Go to Subscription. You don't have anything in your cart right now. The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, engineering design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies.
The book is your one stop guide that introduces you to the functional capabilities of the Scala programming language that are critical to the creation of machine learning algorithms such as dependency injection and implicits.
You start by learning data preprocessing and filtering techniques. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. Finally, the book includes a comprehensive overview of parallel computing in Scala and Akka followed by a description of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala.
His interests include real-time analytics, modeling, and the development of nonlinear models. Sign up to our emails for regular updates, bespoke offers, exclusive discounts and great free content.
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