Uploaded bySuraj Kumar Jana
Artificial Neural Network: A Brief Overview
This document provides an introduction to artificial neural networks, including their basic components like neurons and activation functions. It explains neural networks and how they are trained through backpropagation. Deep learning and common neural network architectures like convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are overviewed.
![Coded Agents – with UiPath SDK + LangGraph [Virtual Hands-on Workshop]](https://cdn.slidesharecdn.com/ss_thumbnails/codedagentsdeck-251215155422-5497c599-thumbnail.jpg?width=640&height=640&fit=bounds)
![Vibe Coding vs. Spec-Driven Development [Free Meetup]](https://cdn.slidesharecdn.com/ss_thumbnails/vibecodingvsspecdrivendevelopment-251209105622-43f455e7-thumbnail.jpg?width=640&height=640&fit=bounds)
Artificial Neural Network: A Brief Overview
- 1.
- 2.
- 3.
- 4. ACTIVATION FUNCTIONS https://opencubelabs.com ● Step Function ●Sigmoid Function ● Tanh Function ● Rectified Linear Unit (ReLU) Function
- 5.
- 6.
- 7.
- 8.
- 9.
- 10.
- 11.
- 12.
- 13.
- 14.