Big Gata - Recommendation Prediction

Inspiration

We wanted to create a project that would minimize clicks for the customer and maximize the user experience. We also wanted to dive into the field of prompt engineering.

What it does

This project used ML models to make predictions on user data. This data can be taken from existing stores of data, or from asking the customer directly. These predictions also include prompts that can be sent to a chatbot or other form of conversational AI.

How we built it

We used primarily python to build it. We divided our team into a front end, back end, and graphic design team. Using tools such tensorflow and tkinter, we were able create a functional product.

Challenges we ran into

We found it challenging to connect the various pieces of code created by all of us. Furthermore, creating data and training a model proved a difficult task.

Accomplishments that we're proud of

We accomplished all of the goals we had in mind, and were able to collaborate successfully as a team to achieve our goals, in time.

What we learned

We learned how to better collaborate together, and how to work together under strict time restrictions. Individually, we learned things such as AI, UI, and graphic design.

What's next for Big Gata - Recommendation Prediction

In the future, we would like to train our model on real, available user data to make more accurate predictions. Adding more parameters is also a future goal of ours.

Built With

• python