Neural Network Fundamentals

Back: Deep Learning

The building blocks of all neural networks: neurons, activation functions, backpropagation, loss functions, optimizers, and normalization techniques. Understanding these is prerequisite to working with any deep learning architecture.

Concepts

• Perceptron
• Activation Functions
• Backpropagation
• Loss Functions
• Optimizers
• Batch Normalization
• Layer Normalization
• Dropout
• Residual Connections

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deep-learning neural-networks fundamentals