Deep Learning in the Cloud and at the Edge
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
Dima Rekesh and Peter Rodriguez
This course provides a hands-on introduction to very large-scale data and the practical issues surrounding how the data is stored, processed, and analyzed, both in the Cloud and on the Edge. Students will work with cloud computing systems, edge devices, large data collections, and high-velocity data streams. The class material will be introduced gradually as it helps students accomplish their projects and assignments throughout the course with exposure to many of the computing applications and technologies in the market. Hands-on activities will enable the students to learn the practical toolkit required to work with data at scale. Deep Learning applications (image / video processing) will serve as the major use case throughout the class.