Stock Market Profit Prediction Using Machine Learning Algorithms and Visualization for Live Data

Stock market prediction analysis is crucial for investors looking to informed decisions about their investments. Stock Market profit prediction is based on the stocks invested. Stock Market plays a major role in our day-to-day life. Based on the trends the stocks vary. The stock market refers to financial concepts. Business and marketing play a major role in the stock market. They mainly concentrate on the demand of the sales or the stocks. Peoples or users mainly follows the current trend of investing in stocks to get the ultimate benefits. This includes various charts, graphs, and numeric representations to identify trends and patterns and identify various important information based on the stock’s dataset. The model is built based on the Live Stocks Dataset which will help to identify predict or analyze the current trends. By this model, users can easily analyze the sales and identify the current stock’s profit. Stock market prediction analysis involves the application of various techniques to forecast future price moments and trends of financial, primarily stocks. These techniques are rooted in quantitative analysis, statistical modeling, and machine learning models. The primary object is to capture patterns and co-relation. There are also other techniques to predict and analyze the stock’s sales which include customer segmentation and targeted marketing, etc. Linear regression models, Decision trees, Random Forests, etc. will help to predict and analyze the sales. The prediction of stock sales is required for Businesses to make decisions and to change market conditions. This paper aims to develop a system that can accurately predict. The model’s performance can be evaluated using metrics such as mean squared error, mean absolute error, and R squared. Once the model is trained and evaluated, it can predict sales of new products or stores. The model is trained by using the Live stocks dataset. By using this model, it gives more than 90% accuracy in predicting the stock’s sales.