Data Science 251
Deep Learning in the Cloud and at the Edge
This hands-on course introduces data scientists to technologies related to building and operating live, high throughput deep learning applications running on powerful servers in the cloud as well on smaller and lower power devices at the edge of the network. The material of the class is a set of practical approaches, code recipes, and lessons learned. It is based on the latest developments in the industry and industry use cases as opposed to pure theory. It is taught by professionals with decades of industry experience.
Working with Data at Scale
Cloud / Distributed Storage / Ethereum Blockchain / Apache Spark / Docker / CouchDB / Apache Cassandra / OpenStack Swift / Apache Solr / BVLC Caffe / Nvidia Digits / Keras / IBM Watson / GATK
Current Course Designer
Original Course Designers
Profile profile for Anonymous
(Until Fall 2018, this course was titled “Scaling Up! Really Big Data.”)
Previously listed as DATASCI W251.
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