|
You are here |
danielegrattarola.github.io | ||
| | | | |
stribny.name
|
|
| | | | | Fields in Artificial Intelligence and what libraries to use to address them. | |
| | | | |
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 ... | |
| | | | |
futurism.com
|
|
| | | | | This post was originally written by Manan Shah as a response to a question on Quora. | |
| | | | |
tcode2k16.github.io
|
|
| | | a random blog about cybersecurity and programming | ||