What is Deep Learning | deep learning - Robotics Tomorrow

Deep learning is a machine learning technique that teaches computers to learn by example just as we learned as a child. We see this technology in autonomous vehicles, explains Len Calderone - Contributing Author.

Photo: Len Calderone

Deep learning is capturing the attention of all of us as it is accomplishing outcomes that were not previously possible.  Deep learning is a machine learning technique that teaches computers to learn by example just as we learned as a child. We see this technology in autonomous vehicles. It enables the vehicle to distinguish between different objects on the road and enables the vehicle to stop when it sees a red light. An autonomous vehicle can determine when it is safe to move forward or to remain stationary.  

In deep learning, a computer becomes proficient at performing tasks from images, text, or sound, and can realize state-of-the-art accuracy, many times exceeding human implementation.

We often hear the terms: AI (artificial intelligence), machine learning and deep learning. So, what are the differences?  All machine learning is AI, but not all AI is machine learning. AI is a general term for any computer program that does something smart. Deep learning is a subset of machine learning, and machine learning is a subset of AI.

Artificial intelligence is an area of computer science that stresses the creation of intelligent machines that work and respond like humans. The basic procedure of machine learning is to provide training data to a learning algorithm, which in turn generates a new set of rules, based on inferences from the data. By using different training data, the same learning algorithm could be used to produce diverse models. Deducing new instructions from data is the strong suit of machine learning. The more data that is available to train the algorithm, the more it learns...

In the past, black and white movie images had to be hand colored, which was very time consuming and costly.  Now this process can be automatically done with deep-learning models, which can automatically colorize grayscale images based on Convolutional Neural Networks, which features a fusion layer that allows an artist to merge local information dependent on small image areas with largescale prior images.

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Source: Robotics Tomorrow