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Stock prediction using machine learning techniques

Ruojun Wang


The goal of this project is to assess and compare various prediction models for stock price forecasting. Initially, we will examine regression and time-series forecasting models to review their performance and accuracy. Subsequently, we will delve into the LSTM model, widely utilized in the quantitative finance domain, to evaluate its effectiveness and determine how it fares in comparison.

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