Backward Pass
The process of computing gradients by propagating error signals backward through the network during training.
Your route here
7 stops · basics first
- Machine Learning ✓ understood
Building systems that learn patterns from data instead of following hand-written rules, getting better at a task as they see more examples.
- Neural Network ✓ understood
A computational model inspired by biological neural networks, consisting of interconnected nodes (neurons) organized in layers that process information through weighted connections.
- Forward Pass ✓ understood
The process of passing input through the network to generate predictions during training or inference.
- Dataset ✓ understood
A collection of data examples used for training, validating, or testing machine learning models.
- Training ✓ understood
The process of fitting a model to data by repeatedly measuring how wrong its outputs are and adjusting its parameters to reduce that error.
- Loss Function ✓ understood
A function that scores how wrong a model's prediction is as a single number, which training then works to make as small as possible.
- Gradient Descent ✓ understood
An optimization method that repeatedly moves a model's parameters a small step in the direction that most reduces the loss.
- Backward Pass · you are here ✓ understood
Where it sits
Leads to
Nothing yet: a destination in its own right.