The Fifth Elephant 2015
A conference on data, machine learning, and distributed and parallel computing
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.
Workshops #
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.
Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
Gs
Gagandeep singh
@gagan-goku
What does your website look like to a web-crawler
Submitted Jun 15, 2015
Section:
Full Talk
Technical level:
Intermediate
The objective of this talk is to go deeper into what site structure is, potential problems with respect to discoverability of your website from the perspective of a web crawler and how to go about fixing it.
Outline #
A case study of what a good website would be from the perspective of a web-crawler that analyzes your website to discover webpages and ranks the best pages for search terms.
Talk covers various ways of computing measures on a link graph and ways of improving it.
Requirements #
Basics of graph theory
Speaker bio #
Gagan is a staff engineer at Bloomreach India. He leads the organic engineering in India and has worked on a bunch of problems relating to the discoverability and relevance of websites from the perspective of search engines. His forté is building applications consuming huge amounts of data to generate meaningful insights.
Prior to Bloomreach, Gagan was an engineer at Google working on Speech recognition, Google maps and web optimization techniques.
Gagan is a B.Tech from IIT Delhi and was ranked 2nd at the Regional Math Olympiad, and a big anime enthusiast.
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Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
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