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The purpose of machine learning is to teach computers to execute tasks without human intervention. machine learning algorithms (not deep learning algorithms) ML Algorithms Grouped by Learning Style      

The main reason for the success is due to deep learning’s strong ability in learning of representations for inputs (i.e., queries, documents, users, and items) and learning of nonlinear functions for matching. Overview of Deep Learning Deep Neural Networks The Feed-forward Neural Networks (FFN), also called Multilayer Perceptron (MLP), are neural networks consisting of multiple layers of units, which are connected layer by layer without a loop. Besides sigmoid function, other functions such as tanh and Rectified Linear Units (ReLU) are also utilized. In learning, training data of input-output pairs are fed into the network as ground-truth. A loss is calculated for each instance by contrasting the ground truth and the prediction by the network, and the training is performed by adjusting the parameters so that the total loss is minimized. The well-known back-propagation algorithm is employed to conduct the minimization. Convolutional Neural Networks (CNN) are neural networks that make us