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@article{155434,
        author = {PRAJIT PAUL and SAYAN BHATTACHARYA and RIMA DAWN and PIJUS PYKE and PARAMITA DAS and SOURAV KUMAR PANDEY and KOUSHIK CHAKRABORTY},
        title = {STOCK PRICE PREDICTION},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {1},
        pages = {833-837},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155434},
        abstract = {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. The paper focuses on the use of Regression and LSTM based Machine learning to predict stock values. Factors considered are open, close, low, high and volume.},
        keywords = {future extraction, NIFTY value prediction, NSE share market, stock market, stock  price prediction},
        month = {},
        }