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@article{152115,
        author = {Abhishek Shukla},
        title = {Stock Prediction Using a Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {2},
        pages = {471-478},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=152115},
        abstract = {Stock prediction is a very important for stock price surveillance. While as a canonical pattern recognition problem, it’s very difficult due to various predictions of stock value of a company. To solve this problem In Stock Market Prediction, the aim is to predict the future value of the financial stocks of a company. The recent trend in stock market prediction technologies is the use of machine learning which makes predictions based on the values of current stock market indices by training on their previous values. Machine learning itself employs different models to make prediction easier and authentic. This focuses on the use of Regression and LSTM based Machine learning to predict stock values. Factors considered are open, close, low, high  and volume. The data stored can be visualized through a web application that uses HTTP GET requests for requesting the data stored in MySQL to a HTML template for rendering dynamic High Charts.},
        keywords = {},
        month = {},
        }