Backpropagation

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• Backpropagation ... FFNN ... Forward-Forward ... Activation Functions ...Softmax ... Loss ... Boosting ... Gradient Descent ... Hyperparameter ... Manifold Hypothesis ... PCA
• Objective vs. Cost vs. Loss vs. Error Function
• Optimization Methods
• Wikipedia
• How the backpropagation algorithm works
• Backpropagation Step by Step
• What is Backpropagation? | Daniel Nelson - Unite.ai
• Other Challenges in Artificial Intelligence
• A Beginner's Guide to Backpropagation in Neural Networks | Chris Nicholson - A.I. Wiki pathmind

The primary algorithm for performing gradient descent on neural networks. First, the output values of each node are calculated (and cached) in a forward pass. Then, the partial derivative of the error with respect to each parameter is calculated in a backward pass through the graph. Machine Learning Glossary | Google