The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships.
One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class.
In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy.
Predicting Stock Price
Financial news corpus is actually far messier than one story implies, for several reasons.
The relevance of a stock to a document may not be clear without a careful reading. With deep parsing we could eliminate some of the noise, but with bag of words we can't hope to remove all.
Started my new ML project:
I will post the update on Tuesday 11th oct