Deep learning is getting a lot of attention these days, and for good reason. It’s achieving unprecedented levels of accuracy—to the point where deep learning algorithms can outperform humans at classifying images and can beat the world’s best GO player.
If you are interested in using deep learning technology for your project, but you’ve never used it before, where do you begin?
Should you spend time using deep learning models or can you use machine learning techniques to achieve the same results? Is it better to build a new neural network or use an existing pretrained network for image classification? What deep learning framework should you use?
This short ebook is your guide to the basic techniques. You’ll see that deep learning is within your grasp—you don’t need to be an expert to get started.
Read the ebook to learn about:
- Machine learning vs. deep learning
- Convolutional neural networks (CNNs)
- Using a pretrained network like GoogLeNet for image recognition and image classification
- Access to examples, tutorials, and software to try deep learning yourself
MATLAB for Deep Learning
Explore MATLAB solutions for deep learning, including videos, product capabilities, examples, and models.
Deep Learning Onramp
Get started quickly using deep learning methods to perform image recognition.
Practical Deep Learning Examples with MATLAB
Learn three approaches to training a deep learning neural network: training from scratch, transfer learning, and semantic segmentation.