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Deep Learning Deep learning works by constructing a model of how to interpret images and video. The model is composed of several layers, with the input layer serving as the training dataset. The hidden layers are then used to extract features from the data and transform them using a linear function. Then, the output layer performs the task. The output layer uses the learned information to create a final prediction and solution. The process is called forward propagation. It has been used by scientists for more than two decades. In its simplest form, Deep Learning uses layers of processing to train computers to identify patterns and recognize the information. The process works by training a computer to detect patterns in data, which is then processed by a series of algorithms. The result is a computer program that learns new information and improves its performance. This approach is very powerful because it allows for the automatic and unsupervised learning process. There are many ben...