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• Instructions: Unsupervised learning is a type of machine learning where the model is trained on a dataset without any labeled output. The goal of unsupervised learning is to identify patterns and relationships in the data, and group similar data points t ... Read More >>
• Neural Network Training: Neural network training is the process of adjusting the weights and biases of a neural network to minimize the difference between the predicted output and the actual output. This is done by feeding the network with a large amount of labeled ... Read More >>
• Expected Cumulative Reward: Expected Cumulative Reward is a concept in Reinforcement Learning that refers to the sum of rewards obtained by an agent over a sequence of time steps, taking into account the probability of each possible outcome. It is used to evaluate the ... Read More >>