Introduction to Deep Learning in Python

Deep structured learning, or hierarchical learning, or simply deep learning, is part of a family of machine learning methods, itself a subset of the broader field of artificial intelligence.

Deep learning is a class of machine learning algorithms that uses several layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output of the previous layer as input.

Deep neural networks, deep belief networks, and recurrent neural networks have been applied to fields such as computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, and bioinformatics, producing results comparable to, and in some cases even better than, those of human experts.

Deep Learning Algorithms and Networks –

• Unsupervised learning based on multiple layers of features or representations of data. Higher-level features are derived from lower-level features to form a hierarchical representation.

• Training is performed using some form of gradient descent.