Hands-On GPU Computing with Python

The advent of deep learning

Deep learning as we know today is a machine learning-based algorithm that mimics the functioning of human brain. The actual foundation of deep learning was laid in the mid-1960s when Alexey Ivakhnenko and his associate, Valentin Grigorʹevich Lapa, used multiple layers of nonlinear features with polynomial activation functions. This was an approach similar to today’s deep learning techniques. It followed by the use of manually weighted neural networks and an application of back-propagation of errors to train deep models that could yield useful distributed representation. Convolutional Neural Networks (CNNs) were introduced in the 1990s specifically for image recognition problems.

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