Perceptrons, Neural Networks and Dynamical Systems

Perceptrons, Neural Networks and Dynamical Systems

Perceptrons, Neural Networks and Dynamical Systems By Sergi Andreu // This post is last part of the “Deep Learning and Paradigms” post Binary classification with Neural Networks When dealing with data classification, it is very useful to just assign a color/shape to every label, and so be able to visualize data in a lower-dimensional plot. The aim of classification is to associate different classes to different regions of the initial space, When using Neural Networks, the initial space is…

Deep Learning and Paradigms

Deep Learning and Paradigms

Deep Learning and Paradigms By Sergi Andreu // This post is the 2nd. part of the “Opening the black box of Deep Learning” post Deep Learning Now that we have some intuition about the data, it’s time to focus on how to approximate the functions that would fit that data. When doing *supervised learning*, we need three basic ingredients: –…

Opening the black box of Deep Learning

Opening the black box of Deep Learning

Opening the black box of Deep Learning By Sergi Andreu Deep Learning is one of the three main paradigms of Machine Learning, and roughly consists on extracting patterns from data using neural networks. Its impact in modern technologies is huge. However, there is not a clear high-level description of what these algorithms are actually doing. In this sense, Deep Learning…