Stock Price Trends Prediction Harnessing Machine Learning Techniques

This project is called “Predicting Stock Price Trends Using Machine Learning Techniques”. This project will be created using the following programming languages: HTML, CSS, and JAVASCRIPT for the front end and PYTHON as the back end. Stock market prediction is the prediction of whether the price of a stock will go up or down or stay the same, and making decisions on buying, selling, or holding a certain stock. Making predictions about stock market trends is a difficult task due to the changing and complicated nature of the financial markets. One way to make predictions about stock market trends is to use a number of different methods, including traditional statistical modeling techniques, and machine learning algorithms. To create a stock price prediction using a Convolutional Neural Network (CNN), you will need to train the CNN algorithm to recognize patterns in the stock price and identify historical stock prices. CNN’s are frequently used for facial and picture recognition, and can also be configured to function like a time series model and predict future stock prices (i.e., predict the stock price based on past stock prices). The process of predicting stock market movement is very similar to predicting the stock price will go up, down or be stable. Machine learning algorithms can also be utilized in this process. Here is a simple example of how you could classify stock market trades using machine learning with a SVM algorithm.