Built-In Training
Train deep learning networks using built-in training functions
After defining the network architecture, you can define training
parameters using the trainingOptions
function. You
can then train the network using trainNetwork
. Use the trained
network to predict class labels or numeric responses.
Apps
Deep Network Designer | Design, visualize, and train deep learning networks |
Functions
trainingOptions | Options for training deep learning neural network |
trainNetwork | Train deep learning neural network |
Topics
App Training
- Train Networks Using Deep Network Designer
Interactively train deep learning networks in Deep Network Designer. - Import Data into Deep Network Designer
Import and visualize data in Deep Network Designer.
Command-Line Training
- Create Simple Deep Learning Neural Network for Classification
This example shows how to create and train a simple convolutional neural network for deep learning classification. - Train Convolutional Neural Network for Regression
This example shows how to fit a regression model using convolutional neural networks to predict the angles of rotation of handwritten digits. - Time Series Forecasting Using Deep Learning
This example shows how to forecast time series data using a long short-term memory (LSTM) network. - Sequence Classification Using Deep Learning
This example shows how to classify sequence data using a long short-term memory (LSTM) network. - Sequence-to-Sequence Classification Using Deep Learning
This example shows how to classify each time step of sequence data using a long short-term memory (LSTM) network. - Sequence-to-Sequence Regression Using Deep Learning
This example shows how to predict the remaining useful life (RUL) of engines by using deep learning. - Sequence-to-One Regression Using Deep Learning
This example shows how to predict the frequency of a waveform using a long short-term memory (LSTM) neural network.