Understanding Compression of Convolutional Neural Nets: Part 1 There are neural network applications where the resources, for example compute power, memory space, battery power etc., are limited. In such.
A common scenario in multiple linear regression is to have a large set of observations/examples wherein each example consists of a set of measurements made on a few independent.
In my previous post, I had written about principal component analysis (PCA) for dimensionality reduction. In PCA, the class label of each and every example, even if available, is.
Any machine learning model building task begins with a collection of data vectors wherein each vector consists of a fixed number of components. These components represent the measurements, known.