The problem The Stock Analyst solves

The goal of this project was to study time-series data and explore as many options as
possible to accurately predict the Stock Price. Through my research we came to know about
Recurrent Neural Nets (RNN) which are used specifically for sequence and pattern
learning. As they are networks with loops in them, allowing information to persist and
thus ability to memorise the data accurately. But Recurrent Neural Nets have vanishing
Gradient descent problem which does not allow it to learn from past data as was
expected. The remedy of this problem was solved in Long-Short Term Memory
Networks , usually referred as LSTMs. These are a special kind of RNN, capable of
learning long-term dependencies.