Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans – learn by example. Venture Beat brought this information to us in their article, “This is what makes deep learning so powerful.”

Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign or to distinguish a pedestrian from a lamppost. It is the key to voice control in consumer devices like phones, tablets, televisions and hands-free speakers.

The success of deep learning comes primarily from the availability of large data sets and computing power. However, it is more than that, which makes deep learning far better than any of the classical machine learning algorithms.

Deep learning is a complex composition of functions from layer to layer finding the function that defines a mapping from input to output. Deep learning is learning a map from input text to output classes – neutral or positive or negative.

It is unfortunate that most organizations have little knowledge of how artificial intelligence (AI) systems make the decisions they do and how the results are applied. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. “Explainable AI” is used to describe an AI model, its expected impact and potential biases.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Data Harmony, harmonizing knowledge for a better search experience.