Deep learning is used to develop models that can find patterns in data. But it isn’t the only method capable of doing this. So when is deep learning the best option for solving practical engineering problems?
Find the answers in this guide, which explores how deep learning can be particularly useful in engineering applications where traditional methods fall short. You will also see how to prepare the data and deep neural networks in order to produce an accurate model in production.
Read this ebook to learn:
- When engineers should use deep learning
- How to collect data (such as images, signal, and sensor data) and augment it with synthetic data
- Techniques for preparing data for a deep neural network
- How to save time with transfer learning
- Practical advice on integrating the model with system logic and deploying to hardware