The key takeaway from this session will be an understanding of the third generation of tools for realizing machine learning algorithms – examples of these tools include Twister, HaLoop, GraphLab. Attendees will also understand why the second generation tools such as Mahout has not implemented some of the machine learning algorithms for big data. The session will also have real-life use cases.
Dr. Vijay Srinivas Agneeswaran has a Bachelor’s degree in Computer Science & Engineering from SVCE, Madras University (1998), an MS (By Research) from IIT Madras in 2001 and a PhD from IIT Madras (2008). He was a post-doctoral research fellow in the LSIR Labs, Swiss Federal Institute of Technology, Lausanne (EPFL) for a year. He has done an internship in Siemens Corporate Research in Bangalore and was with another product development company – Oracle for three years, He subsequently spent a year as principal architect position with GTO, the research arm of Cognizant in Chennai, where he led the Extreme Processing group within the High Performance Computing Centre of Excellence and created Intellectual property in the Big-Data space. He has now taken up the position as Director Technology/Principal Architect as head of the Big-Data R&D at Impetus. He is a professional member of the ACM and the IEEE for the last 7+ years. He has filed patents with US and European patent office’s (with one accepted US patent) and published in leading journals and conferences, including IEEE transactions. His research interests include distributed systems – cloud, grid, peer-to-peer computing as well as machine learning for Big-Data and other emerging technologies.
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