Author: Matteo Alberti Among all tools for the linear reduction of dimensionality PCA or Principal Components Analysis is certainly the main tools of Statistical Machine Learning. Although we focus very often on non-linearity, the analysis of the principal components is the starting point for many analysis (also the core of preprocessing), and […]
Author: Matteo Alberti In this tutorial, we want to open a miniseries dedicated to Manifold-based dimensionality reductions tools. So let’s start by understanding what a Manifold is and when it is important without deepening the underlying mathematics. “Manifold is a mathematical space that on small scale resembles the Euclidean space of a specific dimension” […]
Authors: Francesco Pugliese & Matteo Testi In this post, we are going to tackle the tough issue of the installation, on Windows, of the popular framework for Deep Learning “Keras” and all the backend stack “Tensorflow / Theano“. Installation starts from the need to download the Python 3 package. Let us choose Miniconda and […]
Author: Andrea Mercuri The fundamental type of PyTorch is the Tensor just as in the other deep learning frameworks. By adopting tensors to express the operations of a neural network is useful for two a two-pronged purpose: both tensor calculus provides a very compact formalism and parallezing the GPU computation very easily. Tensors are generally […]