Online Course
CS125x: Advanced Distributed Machine Learning with Apache Spark
This course may be unavailable.
- Provider edX
- Cost Free Online Course (Audit)
- Session Finished
- Language English
- Certificate Paid Certificate Available
- Effort 5-10 hours a week
- Learn more about MOOCs
Taken this course? Share your experience with other students. Write review
Overview
Building on the core ideas presented in Distributed Machine Learning with Spark, this course covers advanced topics for training and deploying large-scale learning pipelines. You will study state-of-the-art distributed algorithms for collaborative filtering, ensemble methods (e.g., random forests), clustering and topic modeling, with a focus on model parallelism and the crucial tradeoffs between computation and communication.
After completing this course, you will have a thorough understanding of the statistical and algorithmic principles required to develop and deploy distributed machine learning pipelines. You will further have the expertise to write efficient and scalable code in Spark, using MLlib and the spark.ml package in particular.
After completing this course, you will have a thorough understanding of the statistical and algorithmic principles required to develop and deploy distributed machine learning pipelines. You will further have the expertise to write efficient and scalable code in Spark, using MLlib and the spark.ml package in particular.
Taught by
Ameet Talwalkar and Jon Bates
Tags
Help Center
Most commonly asked questions about EdX
Reviews for edX's CS125x: Advanced Distributed Machine Learning with Apache Spark Based on 0 reviews
- 5 star 0%
- 4 star 0%
- 3 star 0%
- 2 star 0%
- 1 star 0%
Did you take this course? Share your experience with other students.
Write a review
Never Stop Learning!
