/StockMarketML

Predicting stocks with ML.

Primary LanguageJupyter NotebookMIT LicenseMIT

StockMarketML

Using the magic of machine learning to predict the trends of the stock market.

Tools/libs Used

App

Applying the Model

app screenshot

Lab 3

CollectData

This script gathers headlines/media data from various sources.

MultiHeadlineTickForcasting

Creates and trains a model to predict stock prices based on multiple headlines and historical tick data.

lab 3 model

Lab 2

2nd Attempt

CollectData

This script gathers headlines/media data from various sources.

HeadlineAnalysisAndPrediction

Creates and trains a model to predict stock prices based on headlines.

HeadlineTickAnalysisAndPrediction

Creates and trains a model to predict stock prices based on headlines and historical data.

HeadlineTickAnalysisAndPrediction2

Creates and trains a model to predict stock prices based on headlines and historical data with a slightly different configuration.

MultiHeadlineAndTickPrediction

Creates and trains a model to predict stock prices based on multiple headlines and historical data.

Lab 1

1st Attempt

CollectData

This script gathers data by scraping websites and does basic word processing.

LoadData

This helper script loads the csv files and preprocesses data before being used in a model.

BasicPredictionClassification

This uses a window of the last n stock closes and volumes to predict whether the next close with be high or lower than it opened.

BasicPredictionRegression

This uses a window of the last n stock prices to predict the next close price.

HeadlinePredictionClassification

This uses headlines processed through doc2vec to predict changes in close price.

HeadlineAndTickerClassification

Using historic stock prices and headlines to predict close price.