Deep Learning | 5th | week 2 |.

While Machine Learning is a subset of Artificial Intelligence, Deep Learning is a specialized subset of Machine Learning. Deep Learning layers algorithms to create a Neural Network, an artificial replication of the structure and functionality of the brain, enabling AI systems to continuously learn on the job and improve the quality and accuracy of results. This is what enables these systems to learn from unstructured data such as photos, videos, and audio files. Deep Learning, for example, enables natural language understanding capabilities of AI systems, and allows them to work out the context and intent of what is being conveyed. Deep learning algorithms do not directly map input to output. Instead, they rely on several layers of processing units. Each layer passes its output to the next layer, which processes it and passes it to the next. The many layers is why it’s called deep learning. When creating deep learning algorithms, developers and engineers configure the number of layers and the type of functions that connect the outputs of each layer to the inputs of the next. Then they train the model by providing it with lots of annotated examples. For instance, you give a deep learning algorithm thousands of images and labels that correspond to the content of each image.