A typical ML problem based on NLP put up by ZS Associates on Hackerearth
Given dataset contains data of tweets on various airline’s twitter handles.
It contains a total of 12 columns, out of which one column specifies the sentiment of the tweet. All other columns provide various information related to what was the tweet, where was it posted from, when was it posted, it's retweeted; etc.
Your task is to build a machine learning / deep learning model to predict the sentiment of the tweet using all or some of the other given columns.
I was able to secure a rank of 42 out of 5000+ participants.
