Feature learning or representation learning is a set of techniques in machine learning that learn a transformation of “raw” inputs to a representation that can be effectively exploited in a supervised learning task such as classification. Feature learning algorithms themselves may be either unsupervised or supervised, and include autoencoders, dictionary learning, matrix factorization, restricted Boltzmann machines and various form of clustering. … Feature Learning