Throw back testing, anyone has the idea and wants to know its profitability result. However, in Machine Learning, anyone needs to achieve a result and wants the computer to think instead of him/her to achieve that result with high accuracy.
All technical analysis methods and studies; such as historical support and resistance points, trend line analysis, classic pattern, technical indicators and all trading techniques; lead to how to make money from price action of any instruments (Stocks, Commodities, Currencies, …., etc.).
To determine if a technical method work or not, we should test it on huge data from many and various markets. For example, if anyone desires to test his/her idea over NADAQ, he/she has more than three thousand stocks, or SP500 which includes 500 stocks. We know what Thomas Bulkowski did. he tested the price pattern on the 500 stocks of SP500 to tell us the accuracy percentage of every pattern. So, we need to spend a lot of effort, money and time to just test our idea and to just know if it is effective or not.
Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
Machine learning (ML) is the study of algorithms and mathematical models that computer systems use to progressively improve their performance on a specific task. Machine learning algorithms build a mathematical model of sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is also referred to as predictive analytics.