The code is available on my GitHub page.

Stock Prediction Model (LSTM)

• Created an algorithm that predicts stock prices with an RMS Error as low as .15 for a 5 month period that resulted in 150% return on investments.

• Implemented the use of a web scraper that can collect the historical stock information.

• Visualized the data as a graph and a chart for quicker and more intuitive decision making.

• Scaled and manipulated data in order to increase the model’s prediction accuracy.

• Created data frames in the Python environment and implemented various machine learning APIs such as Tensor Flow, Keras and Pandas.

Web Scraped Information

VIZSF Web Scrape

Predictions Chart

VIZSF chart small

Final Predictions Graph

VIZSF Final Prediction

The code is avaiable on my github page as Stock MLP which can be found using the link at the top of the page.