  This paper tries to address the problem of stock market prediction leveraging
artificial intelligence (AI) strategies. The stock market prediction can be
modeled based on two principal analyses called technical and fundamental. In
the technical analysis approach, the regression machine learning (ML)
algorithms are employed to predict the stock price trend at the end of a
business day based on the historical price data. In contrast, in the
fundamental analysis, the classification ML algorithms are applied to classify
the public sentiment based on news and social media. In the technical analysis,
the historical price data is exploited from Yahoo Finance, and in fundamental
analysis, public tweets on Twitter associated with the stock market are
investigated to assess the impact of sentiments on the stock market's forecast.
The results show a median performance, implying that with the current
technology of AI, it is too soon to claim AI can beat the stock markets.
