Treffer: Scala:Applied Machine Learning

Leverage the power of Scala and master the art of building, improving, and validating scalable machine learning and AI applications using Scala's most advanced and finest featuresAbout This BookBuild functional, type-safe routines to interact with relational and NoSQL databases with the help of the tutorials and examples providedLeverage your expertise in Scala programming to create and customize your own scalable machine learning algorithmsExperiment with different techniques; evaluate their benefits and limitations using real-world financial applicationsGet to know the best practices to incorporate new Big Data machine learning in your data-driven enterprise and gain future scalability and maintainabilityWho This Book Is ForThis Learning Path is for engineers and scientists who are familiar with Scala and want to learn how to create, validate, and apply machine learning algorithms. It will also benefit software developers with a background in Scala programming who want to apply machine learning.What You Will LearnCreate Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizationsDeploy scalable parallel applications using Apache Spark, loading data from HDFS or HiveSolve big data problems with Scala parallel collections, Akka actors, and Apache Spark clustersApply key learning strategies to perform technical analysis of financial marketsUnderstand the principles of supervised and unsupervised learning in machine learningWork with unstructured data and serialize it using Kryo, Protobuf, Avro, and AvroParquetConstruct reliable and robust data pipelines and manage data in a data-driven enterpriseImplement scalable model monitoring and alerts with ScalaIn DetailThis Learning Path aims to put the entire world of machine learning with Scala in front of you. Scala for Data Science, the first module in this course, is a tutorial guide that provides tutorials on some of the most common Scala libraries for data scie