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.
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.
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
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.
Revolutionizing travel with ML & Analytics – An insight into business optimization using Machine Learning and Advanced Analytics
At Orbitz, Big Data technologies have helped transform the way we let people travel. In this talk we elaborate on how we at Orbitz have leveraged intelligence derived from more than 2 PB of semi-structured and unstructured data to optimize various facets of our business such as content optimization, search personalization and channel optimization.
Big data technology is at the heart of our business. Our Travel sites generate about 1 TB of data per day which is stored in HDFS. This data is at the heart of machine learning, advanced analytics and visual analytics. We go over a few case studies which have had a great impact on travel experience for our users and the technology behind them.
- Usage of machine learning to provide personalized sorting of search results which in turn increased the propensity to buy.
- Collecting and analyzing Site experimentation data.
- Marketing Channel Optimization and Campaign effectiveness
- Data platform that enables all of our use cases
Raghu Kashyap serves as the Sr Director of Technology at Orbitz Worldwide. Raghu possesses an extensive background in technology and travel and leads the Data Infrastructure functions at Orbitz Worldwide. Raghu’s team leverages Hadoop extensively to augment traditional BI/DW and unlock the joy of travel for its customers and drive business performance.
Raghu also heads the Bangalore development center of Orbitz which focuses on application development and data science and EDW platform enablement