Stock Price Prediction using SVM and LSTM

  Stock Price Prediction using SVM and LSTM  Predicting how the stock market will perform is one of the most difficult things to do. There are so many factors involved in the prediction – physical factors vs. psychological, rational, global markets, Domestic news, finance events, etc. All these aspects combine to make share prices volatile and very difficult to predict with a high degree of accuracy. using machine learning we can predict stock more accurately and precisely. In this project, we have worked with historical data about the stock prices of a publicly listed company(Tata Motors). We have implemented a mix of machine learning algorithms to predict the future stock price of the company, starting with algorithms like linear regression, SVM and then move on to advanced techniques like LSTM. What is the goal of SVM? Support Vector Machines (SVMs) are mostly used for classification. The goal of an SVM is to define a boundary line between the 2 classes on a graph.  Th...