Implement practical hands-on examples with Apache Spark
About This Video
In this video course, you’ll work through specific recipes to generate outcomes for deep learning algorithms—without getting bogged down in theory. From using LSTMs in generative networks to creating a movie recommendation engine, this course tackles both common and not so common problems so you can perform deep learning in a distributed environment.
In addition, you’ll get access to deep learning code within Spark that you can reuse to answer similar problems or tweak to answer slightly different problems. You’ll learn how to predict real estate value using XGBoost. You’ll also explore how to create a movie recommendation engine using popular libraries such as TensorFlow and Keras. By the end of the course, you'll have the expertise to train and deploy efficient deep learning models on Apache Spark.
The code bundle for this video course is available at https://github.com/PacktPublishing/Advanced-Apache-spark-Deep-learning-recipes
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.