Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN Implementation in PyT

The video tutorial provides a comprehensive guide on using PyTorch for building deep neural networks. It begins with setting up the necessary resources and imports, followed by data preparation using tensors and data loaders. The tutorial then defines a neural network model with multiple layers and activation functions. It explains the setup of an optimizer and loss function, and demonstrates the implementation of a training loop. Finally, it covers making predictions with the trained model and concludes with insights on neural network training.

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