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.
Igniting your data with Apache Spark
Introduce the audience to Spark and it’s API with hands on exercise. The workshop will also deal with deploying and configuring Spark. Finally the workshop will lead into building data applications on top of spark and some lessons from Shopify.
The workshop aims to help the audience understand the architecture of Spark and work with it’s core API. The workshop also aims to help the audience understand how to build and test data applications based on Spark
- Introduction to Spark and in memory computing
- Setting up spark locally
- Spark architecture
- Working with Spark APIs
Spark, a step forward:
- Spark Streaming, Spark SQL, MlLib, Dataframes
- Deploying spark applications
- Building spark applications
- Spark gotchas and best practices
Spark, a deep dive (based on audience interest and if time permits)
- Spark RDDs -> various RDDs that are part of Spark
- Spark and other input sources i.e. Cassandra, hive etc
Basic knowledge of python and hadoop
Yagnik is a software developer at Shopify.