# 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`

or `trainnet`

. Use the trained network to predict class labels or
numeric responses.

## Apps

Deep Network Designer | Design, visualize, and train deep learning networks |

## Functions

## 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.**Create Custom Deep Learning Training Plot**

This example shows how to create a custom training plot that updates at each iteration during training of deep learning neural networks using`trainnet`

.*(Since R2023b)***Custom Stopping Criteria for Deep Learning Training**

This example shows how to stop training of deep learning neural networks based on custom stopping criteria using`trainnet`

.*(Since R2023b)*