Scalable Machine Learning and Data Mining on the Cloud
The bigness of data, and the need for supporting multiple and simultaneous analyses, imply high computational loads and impose immense requirements on storage-CPU communication. Consequently, the need for big data technologies arise that are based on the concept of distributed data and computation, while keeping the principle of data locality. In this project, we approach the general algorithmic issues in scalable systems. Finding solutions to problems that lie at the intersection of scalable systems and their scalable algorithms will reduce latency (wait time for response) in algorithm execution in a distributed cloud environment.