Stock Market Price Prediction Using Machine Learning Techniques | Python Project | Machine Learning | Artificial Intelligence | Image Processing | IEEE (Copy)

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Abstract:

Stock market Price prediction has been an area of interest for investors as well as researchers for many years due to its volatile, complex and regularly changing in nature, making it difficult to make reliable predictions this paper proposes an approach towards prediction of stock market trends using machine learning model. Trading stocks on the stock market is one of the major investment activities. In the past, investors developed a number of stock analysis method that could help them predict the direction of stock price movement. Modeling and predicting of equity future price, based on the current financial information and news, is of enormous use to the investors. Introduction of machine learning caused that new models can be developed based on the past data. Our main hypothesis was that by applying machine learning and training it on the past data, it is possible to predict the closing rate of the stock price. These techniques are used to forecast whether the price of a stock in the future will be higher than its price on a given day, based on historical data while providing an in-depth understanding of the models being used.

Technology:

• python
• pdk
• Machine Learning
• Artificial Intelligence
• MySql

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