Description:

I'll keep it short.

• This talk introduces Kaggle
• Performs a demonstration on the Titanic Competition at Kaggle.
• It touches on the use of Pandas, Numpy, Matplotlib, Seaborn, sk-learn and other libraries.
• It teaches you how to use Jupyter effectively.
• It gives you a gist of what Data Analysis, Machine Learning are all about.
• It illustrates techniques which are important (Cross validation, various scoring methods and so on)

This talk answers the following in roughly the order prescribed:

1. What is Kaggle?
2. Why should I care?
3. What do I need to do this?
4. How do I do it?
5. How do I get better at doing this?

Prerequisites:

• Basic Knowledge of Python Hello-world-like programs.
• How to set up Python on their OS of choice. This includes installing software on the chosen OS
• Some knowledge of Machine Learning / Statistics would help, though it is not necessary.

Content URLs:

Will be released before talk

Speaker Info:

I'm a Masters student at IIITM-K currently working on my Masters' Thesis.
I love building things with Python, blogging, writing articles for OSFY and so on.
I've been swimming in Python for about 5 years now, and absolutely love it.

Speaker Links:

• https://github.com/theSage21
• http://arjoonn.blogspot.in/
• https://twitter.com/arjoonn1