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
Reproduction of code described in the paper "Stock Market Prediction Based on Generative Adversarial Network" by Kang Zhang et al.
Stock Market Forecasting with CoreML in Swift
The main goal of this project is to predict future stock prices using a regression method. I have used two algorithms in this project to build a predictive model, i.e. PSO(Particle Swarm Optimization) and SVM(Support Vector Machine). PSO algorithm is a genetic population-based optimization algorithm that selects the future number using the paramet
Market Analysis and Prediction
web application for finding the best portfolio distribution for the total amount invested by investors in order to maximize their gains and minimize the risks.
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