![]() ![]() To facilitate the accuracy of the prediction, you may separate the data set further in terms of gender and including other elements such as life style, marital status, diet, and so on. Once the training part is done, you can then feed the trained machine with facial images of a new group of people twenty years and see how accurate it can find the facial images of these people today. Use some AI techniques, such as neural networks, to train the computer to find the unknown algorithm of finding the matching facial images of a person twenty years apart. ![]() To do this, you will need two sets of facial images of a group of people, one set consists of facial images of these people twenty year ago, another set their facial images of today. How can you predict the look of a person 20 years from now? One way is to compare the past and the present facial images of many many people, a lot of them, and learn of the differences. It involves the discipline of machine learning. This is more than mere computer programming. ![]()
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