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Machine Learning and Spark

Duration

4 hours

Overview

This course is designed for those working with organizations looking to implement Machine Learning solutions. It is also of benefit for those looking to implement Spark on z/OS. It begins by explaining what Machine Learning is, how it works, and how organizations can benefit from it. The course then focuses on IBM's Machine Learning for z/OS solution, describing its features and components. In the final course, a description of Apache Spark and how it is used in a Machine Learning solution on a z/OS system, is presented.

Audience

The initial module is suitable for anyone requiring a basic understanding of Machine Learning, while later modules are aimed more at application developers, data/business analysts, and information architects, working in a z/OS environment.

Prerequisites

There is no prerequisite for the initial module. A general understanding of the z/OS environment is required for those undertaking the other modules.

Objectives

After completing this course, the student will be able to:

  • How a machine learning solution works
  • The components that comprise IBM's Machine Learning on z/OS solution
  • The purpose of Spark on z/OS, and how it is processes data

Course Content

Introducing Machine Learning

Problems Solved by Machine Learning
Machine Learning Applications
Platforms Supporting Machine Learning
The Machine Learning Process
Algorithms
Supervised and Unsupervised Learning
Reinforcement Learning
Deployment

Machine Learning on z/OS

Types of Data that can be Accessed by a Machine Learning Solution on z/OS
IBM Machine Learning for z/OS Web User Interface
Visual Model Builder
Notebooks Editor
Brunel Visualization Tool
Cognitive Assistant for Data Scientists (CADS)
Supported Algorithms
Components that Comprise IBM Machine Learning for z/OS

Introducing Spark on z/OS

Introduction to Apache Spark
Traditional Spark Features
How Spark on z/OS Accesses z/OS Data
Other Data Spark on z/OS Can Access
Spark on z/OS Features
Standalone Deployment
Client and Cluster Deploy Modes
Spark Processing on z/OS
Data Service Studio

Machine Learning and Spark Mastery Test


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