Disentangling Data Science
Search Results for: neural network
Came across this awesome Youtube video that blew my mind. Definitely a handy resource if you want to explain the inner workings of neural networks. Have a look! Reminded me of my other go-to resource when it comes to explaining neural nets, the playlists by 3Blue1Brown: I’ll surely add these to the other neural network … Continue reading 3D visual representations of common neural network architectures
Did you know that dragonflies are one of the most effective and accurate predators alive? And that while it has a brain consisting of very few neurons. Neuroscientist Greg Gage and his colleagues studied how a dragonfly locks onto its preys and captures it within milliseconds. Actually, a dragonfly seems to be little more than … Continue reading Dragonflies and neural networks
Seth Bling calls himself a video game designer, a hacker and an engineer. You might know him from MarI/O: his neural network that got extremely good to at playing Super Mario Bros. The video below shows the genetic approach Seth used to train this neural network. Seth randomly generated a starting population of neural networks where the … Continue reading Neural Networks play Super Mario Bros & Mario Kart
Last month, a video by 3Blue1Brown has been trending on YouTube, accumulating already over a quarter of a million views. It only lasts 10 minutes but provides a very good and intuitive explanation of the inner workings of Neural Networks (NN): The Machine Learning & Deep Learning book I wrote about recently provides a more substantial explanation of the … Continue reading Neural Networks 101
Coding Train is a Youtube channel by Daniel Shiffman that covers anything from the basics of programming languages like JavaScript (with p5.js) and Java (with Processing) to generative algorithms like physics simulation, computer vision, and data visualization. In particular, these latter topics, which Shiffman bundles under the label “the Nature of Code”, draw me to the … Continue reading Visualizing Neural Networks in Processing
Artificial neural networks (ANNs) are computing systems inspired by the human brain. They can teach themselves to do tasks, simply by considering examples of the tasks’ outcome. For example, they can learn to identify images that contain cats by analyzing example images that have been tagged “cat” or “no cat”. When given enough examples, the … Continue reading R learning: Neural Networks
