Inspiration
As retail investors, we are overwhelmed by the information to evaluate the underlying value of the stock. Our group aims to use Machine Learning to analyze the future performance of the stock.
What it does
Use machine learning to generate a recommendation score for a stock to help user to make a more informed decision to buy/sell stock
How we built it
We using Python as our main programming language. We use various frameworks and packages such as Pytorch for deep learning, and data preprocessing such as Numpy, Pandas, Matplotlib and Scikit-learn
Challenges we ran into
building Stockwise.
Accomplishments that we're proud of
building Stockwise.
What we learned
building Stockwise.
What's next for StockWise
Built With
- dense
- lstm
- matplotlib
- numpy
- python
- pytorch
- scikit-learn
- softmax
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