A machine learning project spans over one and a half month summer course. This project intends to provide hands-on experience with a famous machine learning library, PyTorch, and machine learning techniques, including but not limited to, Logistic Regression, RNN, and LSTM
Team members are welcome to integrate other non-ML techniques to improve the accuracy such as sentiment analysis
The stock market is known to show emerging trends in the way of its computation and it is times of volatility that spontaneous judgments are needed to be made to speculate price behaviour. A platform which trains a predictive model through mining the news for headlines and words pertaining demonstrating an ascertainable correlation to share price changes is exemplary to the application of AI in finance
With the use of recurrent neural networks that incorporate LSTM, logistic regression, naïve bayes, term frequency and a simultaneous focus on political events keeping in mind the obsolete tendency. This attributes to the automation dynamic of the pertinent algorithms that would be amended to such occurrences