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6 days ago · Supervised learning is the most common type of machine learning algorithms. It uses a known dataset (called the training dataset) to train an algorithm with a known set of input data (called features) and known responses to make predictions. The training dataset includes labeled input data that pair with desired outputs or response values.
5 days ago · A neural network (NN) is known to be an efficient and learnable tool supporting decision-making processes particularly in Industry 4.0. The majority of NNs are data-driven and, therefore, depend on training data quantity and quality. The current trend in enhancing data-driven models with knowledge-based models promises to enable effective NNs ...
5 days ago · Ronan Collobert, Jason Weston, A unified architecture for natural language processing: deep neural networks with multitask learning, in: Proceedings of the 25th International Conference on Machine Learning, 2008, pp. 160–167.
5 days ago · Ronan Collobert, Jason Weston, A unified architecture for natural language processing: deep neural networks with multitask learning, in: Proceedings of the 25th International Conference on Machine Learning, 2008, pp. 160–167.
5 days ago · also called an attention network, whose neurons, or meta neurons, receive values from the first network and input signals and produce outputs that alter the values of the controlled network’s synapses. Such a network realizes ANN learning, as depicted in Figure 3, where meta-neurons update weights. Figure 3.
