Jul 2012
23 Mon
24 Tue
25 Wed
26 Thu
27 Fri 09:30 AM – 05:30 PM IST
28 Sat 09:30 AM – 05:00 PM IST
29 Sun
What are your users doing on your website or in your store? How do you turn the piles of data your organization generates into actionable information? Where do you get complementary data to make yours more comprehensive? What tech, and what techniques?
The Fifth Elephant is a two day conference on big data.
Early Geek tickets are available from fifthelephant.doattend.com.
The proposal funnel below will enable you to submit a session and vote on proposed sessions. It is a good practice introduce yourself and share details about your work as well as the subject of your talk while proposing a session.
Each community member can vote for or against a talk. A vote from each member of the Editorial Panel is equivalent to two community votes. Both types of votes will be considered for final speaker selection.
It’s useful to keep a few guidelines in mind while submitting proposals:
Describe how to use something that is available under a liberal open source license. Participants can use this without having to pay you anything.
Tell a story of how you did something. If it involves commercial tools, please explain why they made sense.
Buy a slot to pitch whatever commercial tool you are backing.
Speakers will get a free ticket to both days of the event. Proposers whose talks are not on the final schedule will be able to purchase tickets at the Early Geek price of Rs. 1800.
Hosted by
Jaidev Deshpande
@jaidevd
Submitted Apr 25, 2012
Objectives:
So we have a large data file. We might not know what to do with it. We most probably are looking for patterns and trends. With a multitude of data analysis tools and algorithms at our disposal, we are often left wondering as to what’s the right thing to ask of the data.
Exploratory data analysis is a field which offers tools and algorithms for the most broad, general look at a piece of data. It is after performing this sort of a global analysis on the data that we can go ahead and think about building a model to describe the data. This tutorial offers insights into the prerequisites for building such models, and having gained those, what all one could do with the model.
The tutorial will seek to answer questions like:
I am an electrical engineering undergrad at VIIT, Pune. I’ve been working as a research assistant in the fields of machine learning and signal processing. I am currently working as an intern at Enthought, Inc, where I work on data analysis and visualization. I also contribute code and documentation to the SciPy project.
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