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PyTorch explained: from neural networks to real-world models
This session introduces PyTorch and walks through the core concepts behind modern deep learning models. Starting with an intuitive explanation of neural networks as differentiable functions, we explore how models learn through gradient descent, backpropagation, and nonlinear activation functions like ReLU. The video also covers essential ...
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