UCF Data Analysis and Visualization Bootcamp

Proposal For Final Project

This document contains the proposal for our final project: Predicting future stock prices based on their historic data.

Team Members (Group #4)

• Sam Azhari
• Stephanie Rivas
• Ian Castro
• Jose Robles

Project Proposal

For our final project, we will build an application to analyze and predict the future price of stocks by modeling a couple of company indexes as the model for our ML.

We will be looking at the opening, closing, lowest and highest price of a few indexes (companies), split, train and test their data to come up with a working model and successful prediction.

We will use the following tools :

Data cleaning : Pandas

Visualizations : HTML, CSS, Tableau, plotly

Database : Postgres

Machine Learning: Linear Regression, TensorFlow

Deployment : Heroku

Creating the training dataset

Our ultimate goal for the training data is to have a 'snapshot' of a particular stock at a particular time, and its performance of a determined period of time.

Machine Evaluation

We will evaluate our machine learning findings by comparing our conclusion to last year of our data and compare the accuracy of our model.

Model Presentation

Our Plan is to demonstrate our findings by presenting our codes via Jupyter notebook or VScode, we're also planning on using Tableau for plotting our Stocks graphs and lastly we'll be putting our final results into one website after we had ran our machine Locally and launching it on Heroku.

Data Sets

Historical Stock Prices

Most Popular Historical Data Pages

FB Historical Data

AMZN Historical Data

MSFT Historical Data

TSLA Historical Data

SBUX Historical Data

CSCO Historical Data

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