Theme and format
The Fifth Elephant 2017 is a four-track conference on:
- Data engineering – building pipelines and platforms; exposure to latest open source tools for data mining and real-time analytics.
- 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.
- Hands-on tutorials on data mining tools, and ML platforms and techniques.
- 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:
- Draft slides, mind map or a textual description detailing the structure and content of your talk.
- 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.
- 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.
- Proposals will be filtered and shortlisted by an Editorial Panel.
- Proposers, editors and community members must respond to comments as openly as possible so that the selection processs is transparent.
- Proposers are also encouraged to vote and comment on other proposals submitted here.
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.
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”.
- 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
For more information about speaking proposals, tickets and sponsorships, contact email@example.com or call +91-7676332020.
Gabbar: Machine learning to guard OpenStreetMap
OpenStreetMap is the largest free and open map of the world! An average of 2 million features are touched by volunteers around the world every single day. Amazing isn’t it? The global scale and the local diversity bring in a host of challenges for maintaining a high quality of data on OpenStreetMap.
The Mapbox data team works closely with communities of mappers to validate and protect OpenStreetMap data. In this talk, I will do a deep dive into the diversity of mapping on OpenStreetMap, the intricate and challenging data quality problems, learnings from building open tools to aid mappers and how Gabbar, a machine learning based infrastructure, can guard OpenStreetMap from invalid and suspicious edits.
From this talk, I hope to share how open and collaborative projects like OpenStreetMap and Wikipedia are benefitting from open and collaborative machine learning, the opportunities for us as volunteers to build cool and important technology in the open and use the power of AI for a better world for all of us. The intended audience is people interested and/or practicing machine learning to solve data problems as well as people interested and/or contributing to the tech for open projects like OpenStreetMap and Wikipedia.
Edits in a few minutes on OpenStreetMap
1. OpenStreetMap (OSM)
- OSM is the largest free and open map of the world, the Wikipedia of maps.
- On a typical day, 2 million features are created, half a million modified and a quarter features deleted.
- The OSM community, the heart beat of OpenStreetMap.
- Interesting problems and inherent challenges.
- OpenStreetMap changeset analyzer: https://osmcha.mapbox.com/
- Rule based validation with: https://github.com/mapbox/osm-compare
- Guarding OSM from invalid or suspicious edits.
- Machine learning based infrastructure collaboratively build in the open.
- Development workflow with Python data science tools.
- Learning’s, current model performance and impact.
- Using AI to help make OSM the best map of the world!
- Using open collaborative machine learning for open collaborative projects.
Hey, I am Bhargav Kowshik, a Software Engineer at Mapbox, Bengaluru. I build tools to scale data operations at Mapbox. I am passionate about people and communities, open data and technology, creativity and side projects. Previously as the first engineer at Nextdrop, I helped build a platform to track water availability and consumption. You can contact me at:
- An open database of inconsistent edits observed on OSM: http://www.openstreetmap.org/user/manoharuss/diary/40118
- Preparing accurate history and caching changesets: https://www.openstreetmap.org/user/geohacker/diary/40846
- Common errors and unexplained edits observed: https://www.openstreetmap.org/user/nammala/diary/40338
- Gabbar development and workflow: https://github.com/mapbox/gabbar/