Machine Learning, Distributed and Parallel Computing, and High-performance Computing are the themes for this year’s edition of Fifth Elephant.
The deadline for submitting a proposal is 15th June 2015
We are looking for talks and workshops from academics and practitioners who are in the business of making sense of data, big and small.
Track 1: Discovering Insights and Driving Decisions
This track is about general, novel, fundamental, and advanced techniques for making sense of data and driving decisions from data. This could encompass applications of the following ML paradigms:
- Statistical Visualizations
- Unsupervised Learning
- Supervised Learning
- Semi-Supervised Learning
- Active Learning
- Reinforcement Learning
- Monte-carlo techniques and probabilistic programming
- Deep Learning
Across various data modalities including multi-variate, text, speech, time series, images, video, transactions, etc.
Track 2: Speed at Scale
This track is about tools and processes for collecting, indexing, and processing vast amounts of data. The theme includes:
- Distributed and Parallel Computing
- Real Time Analytics and Stream Processing
- MapReduce and Graph Computing frameworks
- Kafka, Spark, Hadoop, MPI
- Stories of parallelizing sequential programs
- Cost/Security/Disaster Management of Data
Commitment to Open Source
HasGeek believes in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like it to be available under a permissive open source license. If your software is commercially licensed or available under a combination of commercial and restrictive open source licenses (such as the various forms of the GPL), please consider picking up a sponsorship. We recognize that there are valid reasons for commercial licensing, but ask that you support us in return for giving you an audience. Your session will be marked on the schedule as a sponsored session.
If you are interested in conducting a hands-on session on any of the topics falling under the themes of the two tracks described above, please submit a proposal under the workshops section. We also need you to tell us about your past experience in teaching and/or conducting workshops.
Processing large data with Apache Spark
Overview of Apache Spark functionalities with detailed architecture details. We will touch upon Spark Streaming capability for near real time processing.
In this session, Ravi will cover Apache Spark overview with its unique features using in large data systems. He will get more details into Spark EcoSystem,Architecture, Elements and comparison with MapReduce. He will also touch up on its languages support with working demo session.
Ravi is in in IT industry for 11+ years. Ravi works for Cisco as Technical Leader and part of Cisco service team .He completed MS from BITS and BE from University of Madras. He has well experience in building highly distributable systems using multi-tier architecture. His interest on exploring new technologies and tools.
- Mind Map → https://atlas.mindmup.com/2015/06/3bf0aa00f9f601327cdf06dfaff79cf0/spark/index.html