Do you have what it takes to create artificial intelligence, challenge dumps of
data and create meaning out of it? The field of data science is evolving into one
of the fastest-growing and most in-demand fields in the world. Predict-X will
test your ability to understand data, analyze it, and build predictive models. We challenge you to solve real world problems
with all your data science skills.
Predict-X will consist of two problem statements, one of classification type and the other of regression type. Participants will have 21 days to solve these problems.
The competition will be hosted as in-class competition on Kaggle. Predict-X will present its participants with datasets and general information on the contents of datasets.
Predict-X is an online event that will be conducted for 21 days.
There is no restriction on its participation and the participants can
participate from any college as well as any branch.
Two students from different colleges can be a part of the same team.
However, one person cannot be a part of multiple teams for the same event.
Teams who do not register will not be eligible for prizes and their solution
will not be taken under consideration.
The links to the problem statements on Kaggle will be provided after submitting the form in the form itself. Also, please copy the links to somewhere else for future reference.
Rules may be changed without any prior intimation. Participants are
requested to check the MindSpark'18 website (www.mind-spark.org) regularly
Q. What is the evaluation criterion?
A. The evaluation criteria ascends in the following order
1) Accuracy of solution set.
2) Efficiency of the code
Q. Can I participate in other events of MindSpark'18?
A. You are free to participate in as many events as you wish. However, you
have to manage your own schedule.
Q. Do team members have to be from the same college?
A. No, team members can be from any year, any branch and any institution.
However, one person cannot be a part of 2 teams for the same event.
Q. What libraries can I have access to?
A. Any library available for the language you want to use that is supported on Kaggle.
For a basic understanding on what data analytics is all about, check it out.
For a basic understanding of various algorithms used in the field of data analytics, check it out.