Applied Machine & Deep Learning

Contextual AI is just that — not merely a single model addressing a question in isolation — but a holistic system working across a rich and diverse set of data, interpreting the signal in context of its surrounding, what came before, what comes after. It is this additional missing context which affords the intelligence and perspicacious insight, leading to true disruptive innovation.

Artificial Intelligence (AI) refers to systems which can sense, reason, learn, recall and take action in response to their environment and prior experiences. While there is a lot of industry hype over the future benefits and very real risks of autonomous systems, companies today are making significant advances in the areas of assisted and augmented intelligence, as well as more traditional automation.
Machine Learning (ML) is a subset of artificial intelligence that provides systems with the ability to learn and improve from experience without being explicitly programmed.
Deep Learning (DL) is a sub-field of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised, unsupervised and reinforcement based on performance feedback.