##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.
Making data scientists life easy with Docker
Life of data scientists is hard as they have to bother not only about the algorithms & analysis but also about the environment & dependencies they have to build in order to get there at the first place. Also, when it comes to collaboration, deployment and scaling they always have hard times. Introducing docker in the data science workflow can eliminate these issues significantly. While docker has become a boon for devops, it can also be leveraged by data scientists to streamline the whole data science pipeline. So, in the talk, I will give step by step guidelines along with live demos to showcase the use of docker for delivering maximum value as a data scientist.
Audience: All data science professionals and enthusiasts
- A brief outline of docker and its ecosystem
- Why docker is so powerful?
- How docker can be useful for data scientists?
- Building end-to-end data science workflow (with a deep learning use case) using docker.
Abhishek Kumar is an experienced data science professional and technical team lead specializing in building and managing data products from conceptualization to deployment phase and interested in solving challenging machine learning problems.
He holds Master’s degree from University of California, Berkeley. He is also a Pluralsight author and has authored several data science courses that are followed by data science aspirants across the globe. He has worked on various machine learning projects involving predictive modeling, forecasting, optimization, and anomaly detection. He has also received Hal R. Varian award at University of California, Berkeley for his work on deep learning based context recognition system.
He is currently working as SapientRazorfish as Manager, Data Science and focusing on applying methods in machine learning to opportunities in retail, ecommerce, marketing and operational optimization.
- LinkedIn Profile (https://www.linkedin.com/in/meabhishekkumar/ )
- Pluralsight Courses (https://www.pluralsight.com/authors/abhishek-kumar )