Built-In Training
Train deep learning networks for image data 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.
You can train a neural network on a CPU, a GPU, multiple CPUs or GPUs, or in parallel on a cluster or in the cloud. Training on a GPU or in parallel requires Parallel Computing Toolbox™. Using a GPU requires a supported GPU device (for information on supported devices, see GPU Computing Requirements (Parallel Computing Toolbox)). Specify the execution environment using the trainingOptions
function.
App
Deep Network Designer | Progetta, visualizza e addestra le reti di Deep Learning |
Funzioni
Argomenti
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
- Creazione di una rete neurale semplice di Deep Learning per la classificazione
Questo esempio mostra come creare e addestrare una rete neurale convoluzionale semplice per la classificazione tramite Deep Learning. - 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. - Set Up Parameters and Train Convolutional Neural Network
Learn how to set up training parameters for a convolutional neural network. - Deep Learning in MATLAB
Scoprire le capacità del Deep Learning in MATLAB® utilizzando le reti neurali convoluzionali per la classificazione e la regressione, incluse le reti preaddestrate e il transfer learning, nonché l’addestramento su GPU, CPU, cluster e cloud. - Deep Learning Tips and Tricks
Learn how to improve the accuracy of deep learning networks. - Data Sets for Deep Learning
Discover data sets for various deep learning tasks.