Data Science Day @ Columbia University

The advent of deep learning has revolutionized the field of computer vision and machine perception. Deep learning technology combines artificial neural network architectures with massive computing power to perform training and inferences. On a high level, deep learning involves a two stage process: First a neural network is trained by tuning its numeric weights based on experience - i.e. determining its parameters using labeled examples of inputs and desired output. This makes neural nets adaptive to inputs and capable of learning. Second, the network is deployed to run inferences i.e. using its previously trained parameters to classify, recognize, and generally process unknown but similar inputs.[2] GPUs massively parallel capabilities and energy efficiency makes them the state of the art in training deep neural networks as opposed to more traditional CPU based platforms.