Overview
Deep learning model training is a critical process in machine learning that involves teaching a neural network to recognize patterns in data. This is achieved through a series of steps, including understanding the structure of neural networks, implementing backpropagation, and training the model wit...
Key Terms
Example: A neural network can classify images of cats and dogs.
Example: Backpropagation helps reduce the error in predictions.
Example: A model that performs well on training data but poorly on test data is overfitting.
Example: A high learning rate can cause the model to converge too quickly.
Example: Training for 10 epochs means the model sees the data 10 times.
Example: L2 regularization adds a penalty based on the size of the weights.
Related Topics
Convolutional Neural Networks
A specialized type of neural network for processing structured grid data like images.
advancedRecurrent Neural Networks
A type of neural network designed for sequence prediction tasks, such as time series or natural language.
advancedTransfer Learning
A technique where a pre-trained model is adapted to a new but related task.
intermediateKey Concepts
Neural NetworksBackpropagationOverfittingLearning Rate