The anatomy of neural networks
In the first section of this book, we talked about models. These models that we spoke about and used for various use cases are neural networks. A neural network is a deep learning algorithm inspired by the functionality of the human brain, but by no means does it operate like the human brain. It learns useful representation of the input data using a layered approach, as shown in Figure 5.1:
Figure 5.1 – Neural network
Neural networks are ideal for tackling complex problems due to their ability to identify very complex patterns in data. This makes them well suited for building solutions around text and image data (unstructured data), tasks that traditional machine learning algorithms struggle with. Neural networks develop rules to map input data to the target or labels using layered representation. When we train them on labeled data, they learn the patterns and use this knowledge to map the new input data to their corresponding...
