Abstract: Linear discriminant analysis (LDA) is a well-known feature-extraction technique for data analytic and pattern classification. As the dimensionality of multimedia data has increased in this ...
Hosted on MSN
Tutorial; Vernier Video Analysis
Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...
When WarnerMedia and Discovery Inc. merged back in 2022, the rationale was that the combination would put the companies in a better position to compete against Netflix, Disney and others that were ...
ABSTRACT: Quantitative headspace analysis of volatiles emitted by plants or any other living organisms in chemical ecology studies generates large multidimensional data that require extensive mining ...
ABSTRACT: Quantitative headspace analysis of volatiles emitted by plants or any other living organisms in chemical ecology studies generates large multidimensional data that require extensive mining ...
Navigating the complex landscape of single-cell transcriptomic data presents significant challenges. Central to this challenge is the identification of a meaningful representation of high-dimensional ...
In this excellent tutorial video presentation below, Magnus Erik Hvass Pedersen demonstrates the basic workflow of using TensorFlow with a simple linear model. After loading the so-called MNIST ...
Abstract: Component Analysis (CA) methods (e.g. Kernel Principal Component Analysis, Linear Discriminant Analysis, Spectral Clustering) have been extensively used as a feature extraction step for ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results