Concepts(5)
Plain-language explanations of technical ideas.
Activation Functions
The non-linear functions applied after each layer that give neural networks the ability to learn complex patterns.
Deep LearningNeural NetworksArchitecture
Backpropagation
The algorithm that calculates how much each weight in a network contributed to the error, making gradient descent possible at scale.
Deep LearningTrainingNeural Networks
Gradient Descent
The algorithm that teaches a neural network to get better over time by nudging its weights in the right direction.
Deep LearningOptimizationTraining
Transformers
The architecture behind almost every modern AI model, from ChatGPT to translation to image generation.
Deep LearningNLPAttention
Vanishing Gradient Problem
Why deep networks and recurrent models struggle to learn when the error signal fades out before reaching the early layers.
Deep LearningTrainingRNN