I am a Software Engineer, deeply passionate about distributed systems, data engineering and machine learning among others. I work in finance, on risk technologies for automated trading systems after a short stint in a bio informatics startup.
Track: Big Data
"Machine learning (ML) and statistical techniques are crucial to transforming Big Data into actionable knowledge. However, the complexity of existing ML algorithms is often overwhelming for non Machine Learning developers.
MLBase is a platform for non machine learning experts to implement complex machine learning tasks, select and dynamically adapt models and algorithms, in a simple, scalable and declarative way."
Track: OSDC 3
The big data ecosystem has evolved with a myriad of projects, mostly rotating around Hadoop. The Spark project first designed has an extension to the latter, has turned into a full blown ecosystem for lightning fast computations for iterative algorithms on large datasets, an integrated graph processing framework, an in-memory filesystem, a stream processing engine and a new machine learning library that holds the promise of revolutionizing the way we do complex analysis of large data sets. In this talk we will go through the different component of the Spark analytic stack and see why a lot of people have taken a strong interest to it.
Title: Software Engineer