PyTrade

Inspiration

Our biggest inspiration for this app was the Advice Company's category which was: "Most Innovative Use of AI for Personal Finance."

What it does

The application tells you what stocks to invest in based on 3 parameters: risk profile(High risk, Medium Risk, and Low Risk), the desired return type(Low Return, Medium Return, High Return), and the industry the customer wants to invest in. Once the user has entered these 3 inputs the machine learning model is used to figure out which stocks are the best option for the user.

How we built it

We used python Tkinter to create a GUI, excel to manage the dataset, jupyter notebook and TensorFlow to create the machine learning model

Challenges we ran into

We ran into challenges quite often. One of our initial challenges was setting up the GUI to use the machine learning model. Making the machine learning model was also challenging as we have never used TensorFlow before. Also,

Accomplishments that we're proud of

We created a machine learning model, We also created a gui so that anyone can use it.

What we learned

We learned a lot in this project. None of us have ever used tensorflow before to create a machine learning model.

What's next for PyTrade

Our next step for PyTrade is to make the machine learning model better by adding more criteria to our selection process

Built With

• jupyter
• python
• tensorflow
• tkinter