How Artificial Neural Networks Learn (Backpropagation)
Explore the fundamental process of backpropagation in artificial intelligence (AI). This video elucidates how neural networks learn and improve by adapting to data during each training phase. Backpropagation is crucial in calculating errors and updating the network’s weights to enhance decision-making within the AI system. This tutorial breaks down the core mechanics of neural network training, making it easier to understand for individuals interested in AI, machine learning, and network training. By understanding backpropagation, viewers can better grasp how neural networks evolve to process information more accurately. Keywords: rosenblatt, AI, Artificial Intelligence, Neural Networks, Backpropagation, Machine Learning, Network Training, Data Adaptation, Error Calculation, Performance Tuning, Decision Making.
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