Machine Learning with Scala on Spark

Explore machine learning with Scala on Apache Spark in this 39-minute conference talk from Scala Days Berlin 2016. Discover the advantages of Spark.ml over older technologies and compare it to widely used frameworks in R and Python. Learn about the stages of building a predictive model, including exploration, data cleaning, feature engineering, and model fitting. Gain insights into Spark.ml's ease of use, productivity, feature set, and performance. Understand the new capabilities Spark.ml offers to data scientists and machine learning practitioners. Delve into topics such as DataFrame vs DataSet, Scala as the defacto ML language, hyperparameter tuning, ETL processes, and pipeline approaches. Explore the pros and cons of using Spark for machine learning, and get inspired to join the community in using and improving this rapidly maturing technology.