A definition of machine learning for pattern recognition
Machine learning is a broad field within AI that focuses on developing algorithms that allow computers to learn from data and make decisions or predictions, without being explicitly programmed for specific tasks. The primary goal is to enable machines to improve their performance on a given task through experience.
Pattern recognition is a specific application area within the broader field of machine learning. It involves the process of identifying patterns and regularities in data. Pattern recognition is essentially about categorizing or classifying data based on learned patterns.
In my experience, I’ve found that there are numerous similarities between the logic behind machine learning for pattern recognition and those of the traditional technical trading approach.
Every time traders analyze a stock chart, they search, sometimes unconsciously, for a price configuration that they have seen before. If you listen...
