With just a few lines of MATLAB® code, you can build deep learning models without having to be an expert. Explore how MATLAB can help you perform deep learning tasks.
- MATLAB is fast: Run deployed models up to 7x faster than TensorFlow and up to 4.5x faster than Caffe2.
- Easily access the latest models, including GoogLeNet, VGG-16, VGG-19, AlexNet, ResNet-50, ResNet-101, and Inception-v3.
- Use NVIDIA GPUs for your GPU programming: Accelerate training using multiple GPUs, the cloud, or clusters.
- Use functions and tools to visualize intermediate results and debug deep learning models.
- Automate ground-truth labeling using apps.
- Work with models from Caffe and TensorFlow-Keras.
Start Using MATLAB for Deep Learning
Learn how to perform deep learning using MATLAB, a webcam, and a pretrained neural network to identify objects in your surroundings. Watch the video and follow along with the code:
camera = webcam; % Connect to camera nnet = alexnet; % Load neural net while true picture = snapshot(camera); % Take picture picture = imresize(picture,[227,227]); % Resize label = classify(nnet, picture); % Classify image(picture); % Show picture title(char(label)); % Show label drawnow; end
Learn to Use MATLAB for Deep Learning in 2 Hours
Get a hands-on introduction to practical deep learning methods for image recognition. Topics include convolutional neural networks, using pre-trained networks, and transfer learning.