Today, I'll show you how to create a machine learning program to predict stock prices. Machine learning is used in a variety of fields, and we can utilize its ability to learn and predict from data to predict useful variables, with minimal error. Therefore in theory, we can apply the same on stocks to predict the next closing price, so that we can make a killing gain. However, stock markets are highly unstable. Their price movement often depends on decisions taken by the company, favor and reaction of investors, social impact, human emotions, and price movements of some other related stocks. These types of data cannot be made available to a program. The prediction can be close only if the market remains relatively stable. You don't actually need to learn machine learning using python to understand how this program works, if not minimal. I'll describe each machine learning process. And don't forget to download the source code of this program, link provided at the end.