Author: Paolo Caressa Points, vectors and their algebra So far we dealt with points as identified with pairs (or triples for space) of real numbers: as far as Machine Learning is concerned, we are interested infinite sets of points, which represent particular objects to classify or phenomena to correlate as points in a Cartesian […]
Author : Matteo Alberti Sommario Dimensionality Reduction in a linear space. 1 Through the identification of a subspace. 1 Reduction through matrix approximations. 1 Basic case: Decomposition in Singular Values (SVD). 1 Matricial Norms. 1 Vectorial Norms. 1 Induced Norms. 1 Schattern Norms. 1 Frobenius Norms. 1 Base Cases: Cluster Analysis. 1 Definition of […]
Author: Matteo Alberti Sommario Dimensionality Reduction in a linear space. 1 Through the identification of a subspace. 1 Reduction through matrix approximations. 1 Basic case: Decomposition in Singular Values (SVD). 1 Matricial Norms. 1 Vectorial Norms. 1 Induced Norms. 1 Schattern Norms. 1 Frobenius Norms. 1 Base Cases: Cluster Analysis. 1 Definition of […]
Author: Paolo Caressa Foreword In machine learning and deep learning, as in any other interdisciplinary area, concepts and formalisms coming from different sources and fields are used, and often they require different mindsets to be actually understood and properly managed. For this reason, one says usually that a data scientist should be […]