https://www.kaggle.com/c/facebook-recruiting-iii-keyword-extraction/ The code is to solve the above mentioned problem from kaggle. In this code uploaded I am using 1M data points i.e., combination of title and description from the stack overflow dataset and performing logistic regression to predict tags. The metric that is used in this is the F1 Score.
Problem Statement: Stack Overflow is something which every programmer use one way or another. Each month, over 50 million developers come to Stack Overflow to learn, share their knowledge, and build their careers. It features questions and answers on a wide range of topics in computer programming. The website serves as a platform for users to ask and answer questions, and, through membership and active participation, to vote questions and answers up or down and edit questions and answers in a fashion similar to a wiki or Digg. As of April 2014 Stack Overflow has over 4,000,000 registered users, and it exceeded 10,000,000 questions in late August 2015. Based on the type of tags assigned to questions, the top eight most discussed topics on the site are: Java, JavaScript, C#, PHP, Android, jQuery, Python and HTML.
I will be revisiting this and updating this repo again in the future for getting even better results when I finish my research in neural nets.
Till then, hope this helps. If any query please do send me a mail - [email protected]
Thanks.