<p>Programmers face multiple challenges while implementing ML; dealing with unstructured data and picking the proper ML model are among the hardest.</p> <p>In this course we will go through day-to-day challenges that programmers face when implementing ML pipelines and consider different approaches and models to solve complex problems.</p> <p>You will learn about the most effective machine learning techniques and implement them in your favor. You will implement algorithms in practical hands-on projects, building data models and understanding how they work by using different types of algorithm.</p> <p>Each section of the course deals with a specific machine learning problem and analysis and gives you insights by using real-world datasets.</p> <p>By the end of this course, you will be able to take huge datasets, extract features from it, and apply a machine learning model that is well suited to your problem.</p> <p>The code bundle for the course is available at: https://github.com/PacktPublishing/Hands-On-Machine-Learning-with-Scala-and-Spark</p> <h1>Style and Approach</h1> <p>This is a step-by-step and fast-paced guide that will help you learn how to create a ML model using the Apache Spark ML toolkit. With this practical approach, you will take your skills to the next level and will be able to create ML pipelines effectively.</p>