Stock Predictor Model

• 

  ALT

• 

  CELH

• 

  CVNA

• 

  FUBO

• 

  UPST

Inspiration

Our team is comprised of all freshmen who always wanted to try out a hackathon experience. This lead us to join this StockHack and make our model.

What it does

Our code predicts the future values of the stocks provided using a Decision Tree Regression model and plots them to visualize the data.

How we built it

Utilizing real-world stock values from Yahoo Finance we brainstormed various methods of prediction and decided on doing a Decision Tree Regression due to its simple to implement but quite accurate method of prediction.

Challenges we ran into

For all of the team members, this was our first time attempting anything like this, so we had to learn from the ground up all the info we used. There was a lot of issues incorporating the new predicted values and the historical values into the graph to provide a good visual.

Accomplishments that we're proud of

We at the end of the day were happy with our finished product especially since it was our first time doing anything like this.

What we learned

There was a ton that we learned throughout like the strategy and planning required to do a hackathon, stock model prediction methods, github branching/good design philosophy, plotting using matplotlib

What's next for Stock Predictor Model

We plan to utilize the knowledge we gained from this project to continue further into stock prediction by next trying to do a ML model through Pytorch to learn better methods.

Built With

• python