The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Scala programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results.
Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
Scala is a concise, object-oriented language with functional programming features, including currying, type inference, immutability, lazy evaluation, and pattern matching. Scala code runs on a JVM and was designed to address some of the shortcomings of Java.
In this instructor-led, live training participants will learn how to use Scala's advanced features, including its type system, to write better code using an object-functional approach.
By the end of this training, participants will be able to:
Leverage Scala's type system to maximum benefit
Handle exceptions functionally
Create libraries and DSLs with Scala
Use Scala's advanced features for pattern matching
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
Scala is a concise, object-oriented language with functional programming features, including currying, type inference, immutability, lazy evaluation, and pattern matching.
In this instructor-led, live training participants will learn how to use Scala's advanced features to develop well-constructed software that is easy to write, read, test, and change. The focus of this training is on functional programming, using real-world case studies and discussion as a reference for lab exercises and activities.
By the end of this training, participants will be able to:
ScalaCheck is a library for carrying out automated, propertybased testing for Scala or Java programs Inspired by the Haskell library QuickCheck, it uses properties to describe the expected behavior of an application, generating random input data at first, then testing this data across different areas of the application and reporting the result
In this instructorled, live training, participants will learn the benefits of and concepts behind propertybased testing as they practice writing properties that lead to the automatic generation of test cases
By the end of this training, participants will be able to:
Write general properties that replace and/or compliment handwritten unit test cases
Write tests at the higher level of property specifications
Execute ScalaCheck as a standalone executabl, using the builtin command line test runner
Integrate ScalaCheck with test frameworks such as ScalaTest, specs2 and LambdaTest
Audience
Test engineers
Developers
Format of the course
Part lecture, part discussion, exercises and heavy handson practice
.
This training outline is intended to bring attendees from a beginner to an intermediate/advanced level in the understanding and knowledge of the Akka framework.
The entire course is hands on, mostly driven by the trainer in the beginning and progressively shifting towards the attendees producing code themselves (and downloading implementations/solutions written by the trainer).
Attendees are not expected to have prior knowledge of Scala, the trainer will take the necessary time to explain and clarify all the intricacies that relate to the Scala code used.
This instructor-led, live training in the Philippines (online or onsite) is aimed at software engineers who wish to stream big data with Spark Streaming and Scala.
By the end of this training, participants will be able to:
Create Spark applications with the Scala programming language.
Use Spark Streaming to process continuous streams of data.
Process streams of real-time data with Spark Streaming.
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