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Deep learning is a sub-branch of machine learning. It is also recognized as the most powerful alternative to machine learning. It can perform more complex operations with fewer data. In addition, while feature selection is performed manually in traditional machine learning algorithms, this process is automatic in deep learning. The working principle of deep learning algorithms is the working principle of the brain. It is based on densely multilayered neural networks, but constrained Boltzman machines and probabilistic graph models are also associated with deep learning. These are the methods that work with large amounts of data and reach the final output by further improving the results in each layer. It is supervised, unsupervised, or semi-supervised in terms of the type of education. Its prominent algorithms are convolutional neural network (CNN) and recurrent neural network (RNN). Deep learning models have found use in many areas from natural language processing to image processing.