Create a computer vision system using decision tree algorithms to solve a real-world problem : ANN Training and dataset

The video tutorial delves into the training of artificial neural networks, exploring how they learn and the various strategies involved, such as supervised, unsupervised, and reinforced learning. It explains the process of training and testing neural networks, emphasizing the importance of minimizing errors and avoiding overfitting. The tutorial also discusses the significance of generalization and the challenges of local minima in training techniques.

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