Scalable Machine Learning is a free online course conducted by the University of California, Berkeley. The course deals with the underlying principles required to develop scalable machine learning pipelines and gain hands-on experience using Apache Spark.
About the course
This course introduces the underlying statistical and algorithmic principles required to develop scalable real-world machine learning pipelines. The course presents an integrated view of data processing by highlighting the various components of these pipelines, including exploratory data analysis, feature extraction, supervised learning, and model evaluation.
June 29, 2015
For further information and to register, click here.