This 1-day course is aimed at the practitioning data scientist who is eager to get started with deep learning, as well as software engineers and technical managers interested in a thorough, hands-on overview of deep learning and its integration with Apache Spark.
The course covers the fundamentals of neural networks, transfer learning, and how to build distributed Tensorflow models on top of Spark DataFrames. Throughout the class, you will use Keras, Tensorflow, Deep Learning Pipelines, and Horovod to build and tune models. This course is taught entirely in Python.
Each topic includes lecture content along with hands-on labs in the Databricks notebook environment.
After taking this class, students will be able to:
Engineers, data scientists, team leads, or managers who want to quickly gain an intuition and a practical understanding of recent trends in deep learning, including which problems are suited to deep learning and standard deep learning approaches to these problems.