Jitesh Kumar Meena
ABSTRACT
As observed in numerous sectors, forecasting of stock price is one of the most complicated machine learning tasks. According to the study, there are a huge number of elements that influence supply and demand. The technical analysis of numerous tactics utilized. The emphasis of this research is on how to anticipate the price of a stock in the past, as well as how to analyze for optimization. Time-series data is used to represent stock values while, neural networks are employed to gain patterns from trend. In addition to the numerical study of stock movement, public sentiment is being studied by analyzing textual content from blogs and online news outlets. This study illustrates the use of machine and deep learning models for predicting stock values by analyzing past data.
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