Scala programming language allows you to implement machine learning algorithms and assess their performance
About This Video
- Learn how to extract ML from unstructured data and build models using it.
- Spark's powerful ML toolkit is available to help you build models. Learn how to choose the right model for your problem.
- Apache Spark allows you to use Deep Learning methods to stay at the forefront of ML techniques
Programmers face many challenges when implementing ML. Unstructured data is one of the most difficult.
This course will cover the day-to-day challenges programmers face when implementing ML-pipelines and discuss different models and approaches to solving complex problems.
You will learn the most efficient machine learning techniques and how to implement them in your favor. Practical hands-on projects will be used to implement algorithms. Data models will be built and data analyzed.
Each section of this course focuses on a specific machine-learning problem and provides insights using real-world data.
You will be able take large datasets and extract the features to create a machine learning model that is suited to your problem by the end of this course.
The code bundle for the course is available at: https://github.com/PacktPublishing/Hands-On-Machine-Learning-with-Scala-and-Spark
Downloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
