Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: DNN What is Loss Function

The video tutorial covers activation functions in PyTorch, explaining how they can be implemented using Numpy or torch tensors. It delves into the concept of loss functions, their importance in neural networks, and how they help optimize parameters for better performance. The tutorial discusses various types of loss functions, such as squared loss and cross-entropy loss, and introduces the training process using gradient descent. The next video will demonstrate implementing a loss function in PyTorch, followed by a detailed discussion on gradient descent.

What are some common types of loss functions used in neural networks?

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Describe the process of how a neural network learns from training data.

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What is gradient descent and how does it relate to training neural networks?

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