Big Data Machine Learning Ai & Investing How do you use a Machine Learning Artificial Intelligence model to make investments?
More formally, every machine learning algorithm depends on 3 things which need to be able to be programmed.
Firstly, there needs to exist an experience set, sometimes called a training set. This is data that the algorithm will “learn” from.
Secondly, there needs to be some task, some action that we’re trying to make the machine do. For example a task could be playing a game of chess, predicting the outcome of a game, predicting a stock return.
Lastly, and finally there needs to be some performance measure.
Some way for the algorithm to be able to differentiate between two different ways of completing a task. In general, a machine learning algorithm attempts to find it’s own rules and methods in order to optimize its performance measure.
Moreover, it is very important not to over optimize our alogorithm. Furthermore, let the system learn, but don’t let it adapt too specifically to a market. It must hagve its own, independent model on investing. One based on a theory or decision that the designers have made. Machine Learning does not solve the problem, it optimizes it.
