/explore
|
You are here 
|
natureofcode.com | ||
| | | | |
ujjwalkarn.me
An Artificial Neural Network (ANN) is acomputational modelthat is inspired by the way biological neuralnetworks inthe human brain process information. Artificial Neural Networks have generated a lot ofexcitement in Machine Learning research and industry, thanks to many breakthrough results in speech recognition, computer vision and text processing. In this blog post we will try to... |
|
| | | | | ||
| | | | |
programminghistorian.org
[AI summary] The text provides an in-depth explanation of using neural networks for image classification, focusing on the Teachable Machine and ml5.js tools. It walks through creating a model, testing it with an image, and displaying results on a canvas. The text also discusses the limitations of the model, the importance of training data, and suggests further resources for learning machine learning. |
|
| | | | | ||
| | | | |
matt.might.net
[AI summary] This text explains how a single perceptron can learn basic Boolean functions like AND, OR, and NOT, but fails to learn the non-linearly separable XOR function. This limitation led to the development of modern artificial neural networks (ANNs). The transition from single perceptrons to ANNs involves three key changes: 1) Adding multiple layers of perceptrons to create Multilayer Perceptron (MLP) networks, enabling modeling of complex non-linear relationships. 2) Introducing non-linear activation functions like sigmoid, tanh, and ReLU to allow networks to learn non-linear functions. 3) Implementing backpropagation and gradient descent algorithms for efficient training of multilayer networks. These changes allow ANNs to overcome the limitations of ... |
|
| | | | | ||
| | | | |
comsci.blog
In this blog post, we will learn about vision transformers (ViT), and implement an MNIST classifier with it. We will go step-by-step and understand every part of the vision transformers clearly, and you will see the motivations of the authors of the original paper in some of the parts of the architecture. |
|
| | | |||
