Project Description: Forecasting Tesla’s stock price based on historical sales data Group Members:
- Robert Motta
- Vasudha Nair
- Eddie Xu
- Joshua Sohan
Proposal: Using the 2010 -2020 Tesla dataset, we would like to assess the historical stock data , train our model to predict future stock prices for Tesla and compare and contrast other electric vehicles(EVs) for our overall company analysis.
- Here’s is where we will get the data from:
https://www.kaggle.com/timoboz/tesla-stock-data-from-2010-to-2020
https://afdc.energy.gov/data/ (U.S. Plug-in Electric Vehicle Sales by Model)
https://www.bts.gov/content/gasoline-hybrid-and-electric-vehicle-sales
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Here’s how we will store the data: GitHub
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Here’s what we will do with the data (Getting from Point A to Point B):
a. Use Pandas/ETL/PostgreSQL/ to clean the data and print the clean data b. Use Machine Learning(SKLearn) to forecast the future Tesla sales or Tesla’s stock prices.
c. Use Tableau to produce visualizations to display our historical data.
1. Stock Visuals: https://public.tableau.com/profile/robert.motta#!/vizhome/tesla_stock_viz/TeslaStockData?publish=yes
2. Sales visuals: https://public.tableau.com/profile/robert.motta#!/vizhome/tesla_stock_viz/TeslaStockData?publish=yes
3. Forecast Visuals: https://public.tableau.com/profile/robert.motta#!/vizhome/tesla_forecast/StockForecast
d. Use Heroku to deploy our website(https://tesla-analysis.herokuapp.com/)
i. Use Flask/CSS/HTML to program our website. ii. Use Tableau to embed the visualisation in HTML