When it comes to using machine learning in the stock market, there are multiple approaches a trader can do to utilize ML models. From determining future risk to predicting stock prices, machine learning can be used for virtually any kind of financial modeling. In our previous articles, we delved into the usage of two Time Series models: SARIMAX and Facebook Prophet. We utilized both of these models to forecast the potential, future prices of Bitcoin. In another article, we used classification models to classify stocks based on their performance in quarterly reports.

The inventor of the first neurocomputer, Dr. Robert Hecht-Nielsen, defines a neural network as – "...a computing system made up of a number of simple, highly interconnected processing elements, which process information by their dynamic state response to external inputs." Artificial neural networks are one of the most important tools used in machine learning. They are brain-inspired systems which are designed for reproducibility and the repetition of a test or complete experiment that we learn. Neural networks help us cluster and classify. Typically, a neural network is initially trained, or fed large amounts of data.