Joseph Kambourakis introduces you to Apache Spark 2.0 core concepts with a focus on Spark’s machine learning library, using text mining on real-world data as the primary end-to-end use case. Join Joseph to explore and wrangle data using Spark’s DataSet and DataFrame abstractions. You’ll use the Spark ML API to build an ML pipeline to transform free text into useful features via Spark ML’s Transformer abstraction (e.g., one-hot encoding and term frequency counting) and learn about model selection, training and fitting, and validation and inspection, as well as parameter tuning with grid search parameter selection.
The class will consist of approximately 50% hands-on programming labs in Scala and 50% lecture and discussion.
Joseph Kambourakis is a data science instructor at Databricks. Joseph has more than 10 years of experience teaching, over five of them with data science and analytics. Previously, Joseph was an instructor at Cloudera and a technical sales engineer at IBM. He has taught in over a dozen countries around the world and been featured on Japanese television and in Saudi newspapers. He is a rabid Arsenal FC supporter and competitive Magic: The Gathering player. Joseph holds a BS in electrical and computer engineering from Worcester Polytechnic Institute and an MBA with a focus in analytics from Bentley University. He lives with his wife and daughter in Needham, MA.
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