Using AWS Deep Learning Containers to train an ML model
At this point, you might be wondering what makes a deep learning model different from other ML models. Deep learning models are networks of interconnected nodes that communicate with each other, similar to how networks of neurons communicate in a human brain. These models make use of multiple layers in the network, similar to what we have in the following diagram. Having more layers and more neurons per layer gives deep learning models the ability to process and learn complex non-linear patterns and relationships:
Figure 3.5 – Deep learning model
Deep learning has several practical applications in natural language processing (NLP), computer vision, and fraud detection. In addition to these, here are some of its other applications and examples as well:
- Generative Adversarial Networks (GANs): These can be used to generate realistic examples from the original dataset, similar to what we had...
