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

Shashi Gowda

@g0wda

Escher - democratizing beautiful visualizations

Submitted Jun 12, 2015

I aim to introduce the audience to Escher.jl - a new tool for web-based interactive visualizations wholly programmable in a single, data-friendly, fast, lanugage - Julia. Hopefully, the pleasant ergonomics of the library will encourage data scientists to create more explorable, beautiful, and insightful presentations of data, and also create user interfaces without an army of front-end developers.

Outline

Escher.jl is a tool that lets you create and deploy web-based user interfaces flush with plots of data, infographics, rich-text, mathematical typesetting, and TeX-style layouts. All of which can update dynamically as the data changes. The user only needs to work with one language - Julia. The overhead of writing HTML, CSS and JavaScript disappears, and the web is accessible to the average data scientist. What’s more, the interfaces made with Escher look great by default.

Speaker bio

I am Shashi, I can be found at https://github.com/shashi and https://twitter.com/g0wda. I build user interface tools for the Julia community. Of late, I have been working on Escher, on which my talk is going to be about.

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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