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Apache Spark™ is a fast and general engine for large-scale data processing, with built-in modules for streaming, SQL, machine learning and graph processing. This course shows how to use Spark’s machine learning pipelines to fit models and search for optimal hyperparameters using a Spark cluster.
About This Course
Put your Scala knowledge to good use by tackling Big Data analytics problems. Learn to leverage the integration of Apache Spark™ and Scala. Learn how use Spark’s machine learning pipelines to fit models and search for optimal hyperparameters using Scala in a Spark cluster.
1. General understanding of Scala
2. Experience with Java (preferred), Python, or another object oriented language
3. General understanding of machine learning
Instructor: Dr Priya Dev
Dr Priya Dev is a lecturer of statistics at ANU and UNSW and also a founder of a mobile commerce startup, Qhopper. She completed a PhD in probability theory from ANU and Columbia University and has been a data analytics consultant to ASX listed companies and global banks. Qhopper is a massively scalable mobile commerce platform built on the Lightbend platform using Scala and Spark. It bridges the technology gap for hospitality businesses, helping them create better experiences and connect with new and existing customers through their own online ordering, CRM and business intelligence suite.
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Data Science with Scala- Curriculum 0/1
- Data Science with Scala 06 hourLecture1.1