January 27th, 2020
Last time we covered what the difference between AI and ML.
Deep learning, in turn, is a sub-category of ML. Specifically, it is a class of machine learning algorithm. It is one of the most complex forms of computational information processing as all deep learning systems mimic the way neurons in the human brain help to process complex information. Almost all deep learning applications are based on artificial neural networks. There are many different types of neural networks. Two of the most common that are brought up in conversation are Convolutional Neural Networks (CNNs) and Adversarial Neural Networks (ANNs).
The term ‘deep’ in ‘deep learning’ refers to the number of layers through which data is transformed.
Deep learning is most commonly used in advanced natural language processing and image recognition (for example, the military tank identification AI mentioned earlier, which is based on a real application in the US Military in the 1950s whereby the AI kept recognizing the time of day in images instead of tanks, causing very poor accuracy results in an early experiment of training an artificial neural network).
For more information on Convolutional Neural Networks (CNNs) check out this video here For more information on Adversarial Neural Networks (ANNs), also known as Generative Adversarial Networks (GANs) check out this video here