Understanding deep learning basics
In this part, we explain what neural network and deep neural networks are, what is the motivation for using them, and the different types (architectures) of deep learning models.
What is a neural network?
Neural networks are a subfield of artificial intelligence (AI) and ML that focuses on algorithms inspired by the structure and function of the brain. It is also known as “deep” learning because these neural networks often consist of many repetitive layers, creating a deep architecture.
These DL models are capable of “learning” from large volumes of complex, high-dimensional, and unstructured data. The term “learning” refers to the ability of the model to automatically learn and improve from experience without being explicitly programmed to do so for any one particular task of the tasks it learns.
DL can be supervised, semi-supervised, or unsupervised. It’s used in numerous applications...
