The Fifth Elephant 2017

On data engineering and application of ML in diverse domains

Theme and format

The Fifth Elephant 2017 is a four-track conference on:

  1. Data engineering – building pipelines and platforms; exposure to latest open source tools for data mining and real-time analytics.
  2. Application of Machine Learning (ML) in diverse domains such as IOT, payments, e-commerce, education, ecology, government, agriculture, computational biology, social network analysis and emerging markets.
  3. Hands-on tutorials on data mining tools, and ML platforms and techniques.
  4. Off-the-record (OTR) sessions on privacy issues concerning data; building data pipelines; failure stories in ML; interesting problems to solve with data science; and other relevant topics.

The Fifth Elephant is a conference for practitioners, by practitioners.

Talk submissions are now closed.

You must submit the following details along with your proposal, or within 10 days of submission:

  1. Draft slides, mind map or a textual description detailing the structure and content of your talk.
  2. Link to a self-record, two-minute preview video, where you explain what your talk is about, and the key takeaways for participants. This preview video helps conference editors understand the lucidity of your thoughts and how invested you are in presenting insights beyond your use case. Please note that the preview video should be submitted irrespective of whether you have spoken at past editions of The Fifth Elephant.
  3. If you submit a workshop proposal, you must specify the target audience for your workshop; duration; number of participants you can accommodate; pre-requisites for the workshop; link to GitHub repositories and documents showing the full workshop plan.

About the conference

This year is the sixth edition of The Fifth Elephant. The conference is a renowned gathering of data scientists, programmers, analysts, researchers, and technologists working in the areas of data mining, analytics, machine learning and deep learning from different domains.

We invite proposals for the following sessions, with a clear focus on the big picture and insights that participants can apply in their work:

  • Full-length, 40-minute talks.
  • Crisp, 15-minute talks.
  • Sponsored sessions, of 15 minutes and 40 minutes duration (limited slots available; subject to editorial scrutiny and approval).
  • Hands-on tutorials and workshop sessions of 3-hour and 6-hour duration where participants follow instructors on their laptops.
  • Off-the-record (OTR) sessions of 60-90 minutes duration.

Selection Process

  1. Proposals will be filtered and shortlisted by an Editorial Panel.
  2. Proposers, editors and community members must respond to comments as openly as possible so that the selection processs is transparent.
  3. Proposers are also encouraged to vote and comment on other proposals submitted here.

Selection Process Flowchart

We will notify you if we move your proposal to the next round or reject it. A speaker is NOT confirmed for a slot unless we explicitly mention so in an email or over any other medium of communication.

Selected speakers must participate in one or two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.

There is only one speaker per session. Entry is free for selected speakers.

Travel grants

Partial or full grants, covering travel and accomodation are made available to speakers delivering full sessions (40 minutes) and workshops. Grants are limited, and are given in the order of preference to students, women, persons of non-binary genders, and speakers from Asia and Africa.

Commitment to Open Source

We believe in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like for it to be available under a permissive open source licence. If your software is commercially licensed or available under a combination of commercial and restrictive open source licences (such as the various forms of the GPL), you should consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support the conference in return for giving you an audience. Your session will be marked on the schedule as a “sponsored session”.

Important Dates:

  • Deadline for submitting proposals: June 10
  • First draft of the coference schedule: June 20
  • Tutorial and workshop announcements: June 20
  • Final conference schedule: July 5
  • Conference dates: 27-28 July

Contact

For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.


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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

Srini V. Srinivasan

@drvsrinivasan

Fraud Detection & Risk Management in Payment Systems implemented using a Hybrid Memory Database

Submitted Apr 27, 2017

In this talk, we will describe key real-time use cases in the areas of fraud detection, risk management and revenue assurance for payment systems and other such related systems. We will then present a brief overview of a database platform that has proven to be well suited for handling such use cases.

In payment systems, detecting fraud as it happens is critical to maintaining the integrity of the business. This could mean that for each payment transaction, several components in the payment chain have to be both monitored in real time and analysed for anomalies based on recent historical data to enable a decision to be made in 200-500 milliseconds.

In trading systems, there is a need to constantly calculate risk on a database of changing customer positions (due to both trades and fluctuations in stock values). These calculations are critical in enabling a better user experience by allowing faster, higher quality decisions such as whether to grant margin loans.

In telecommunication systems (and real-time adtech systems), revenue assurance requires the system to provide accurate real-time billing and charging on network data 10-100 times the scale of that which was required just a few years ago.

We have found that the best way to handle the demanding workloads of these types of real-time decisioning use cases is to use a hybrid memory database platform that uniquely leverages DRAM with flash storage. This platform needs to smoothly scale out processing across multiple nodes and optimize the usage of CPUs, DRAM, SSDs and networks to efficiently scale up performance on a single node. Over the past six years, this technology has been continuously used in over a hundred successful production deployments, as many enterprises have discovered that it can substantially improve their business capabilities and enhance their users’ experience.

Outline

https://drive.google.com/file/d/0B80IhwYPI7JWcWM0VVUzNGNHTkU/view?usp=sharing

Speaker bio

Dr. Srini V. Srinivasan is Founder and Chief Development Officer at Aerospike.

When it comes to databases, Srini is one of the recognized pioneers of Silicon Valley. He has two decades of experience designing, developing and operating high scale infrastructures. He has over 25 patents in database, web, mobile and distributed systems technologies. His career includes high-profile technical and executive management roles at IBM, Liberate and Yahoo!.

Srini co-founded Aerospike to solve the scaling problems he experienced with Oracle databases at Yahoo! where, as Senior Director of Engineering, he had responsibility for the development, deployment and 24×7 operations of Yahoo!’s mobile products. Srini is an M.S./ Ph.D. holder from the University of Wisconsin-Madison and is an alumnus of IIT Madras.

Slides

https://drive.google.com/file/d/0B80IhwYPI7JWcWM0VVUzNGNHTkU/view?usp=sharing

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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