Reproduction of code described in the paper "Stock Market Prediction Based on Generative Adversarial Network" by Kang Zhang et al.
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Updated
Jun 12, 2020 - Jupyter Notebook
#
stockmarketforecaster
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Stock Market Forecasting with CoreML in Swift
swift
ios
machinelearning
linearregression
coreml
createml
stockmarketforecasting
stockmarketforecaster
multivariatelinearregression
tabularregressor
applemachinelearning
presentforecasting
dynamicallyloadmlmodel
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Updated
Jun 3, 2020 - Swift
Predict whether a stock price will increase based on headlines on a specific day. Data is Wrangled and Merged for modeling. The bag of words approach is used to vectorize textual data. A combination of NLP and ML models like RanfomForestClassifier is used to predict final results, plus the Naive Bayes approach with NLP to predict the results.
naive-bayes-classifier
nlp-machine-learning
bagofwords
datapreprocessing
stockmarketforecaster
randomforestclassifier
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Updated
Apr 21, 2021 - Jupyter Notebook
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