[[https://www.ibm.com/cloud/learn/neural-networks| Neural Networks ]]

Neural networks reflect the behavior of the human brain, allowing computer programs to recognize patterns and solve common problems in the fields of AI, machine learning, and deep learning.
What are neural networks?

Neural networks, also known as artificial neural networks (ANNs) or simulated neural networks (SNNs), are a subset of machine learning and are at the heart of deep learning algorithms. Their name and structure are inspired by the human brain, mimicking the way that biological neurons signal to one another.

Artificial neural networks (ANNs) are comprised of a node layers, containing an input layer, one or more hidden layers, and an output layer. Each node, or artificial neuron, connects to another and has an associated weight and threshold. If the output of any individual node is above the specified threshold value, that node is activated, sending data to the next layer of the network. Otherwise, no data is passed along to the next layer of the network.

https://www.youtube.com/watch?v=bfmFfD2RIcg

Neural Network In 5 Minutes



https://en.wikipedia.org/wiki/Artificial_neural_network

Artificial neural network

https://www.javatpoint.com/artificial-neural-network


Artificial Neural Network Tutorial

https://www.techopedia.com/definition/5967/artificial-neural-network-ann

Artificial Neural Network (ANN)


https://www.techtarget.com/searchenterpriseai/definition/neural-network

What is a neural network? Explanation and examples 


https://www.analyticsvidhya.com/blog/2021/05/beginners-guide-to-artificial-neural-network/


Beginners Guide to Artificial Neural Network


https://en.wikipedia.org/wiki/Convolutional_neural_network

Convolutional Neural Network

https://towardsdatascience.com/a-comprehensive-guide-to-convolutional-neural-networks-the-eli5-way-3bd2b1164a53


A Comprehensive Guide to Convolutional Neural Networks — the ELI5 way


https://www.ibm.com/cloud/learn/convolutional-neural-networks

 Convolutional Neural Networks 

https://www.mathworks.com/discovery/convolutional-neural-network-matlab.html



What is a Convolutional Neural Network?
3 things you need to know

A convolutional neural network (CNN or ConvNet), is a network architecture for deep learning which learns directly from data, eliminating the need for manual feature extraction.

CNNs are particularly useful for finding patterns in images to recognize objects, faces, and scenes. They can also be quite effective for classifying non-image data such as audio, time series, and signal data.

Applications that call for object recognition and computer vision — such as self-driving vehicles and face-recognition applications — rely heavily on CNNs.


https://cs231n.github.io/convolutional-networks/

CS231n Convolutional Neural Networks for Visual Recognition


https://www.youtube.com/watch?v=zfiSAzpy9NM


Simple explanation of convolutional neural network | Deep Learning Tutorial 23 (Tensorflow & Python)


https://www.youtube.com/watch?v=YRhxdVk_sIs

Convolutional Neural Networks (CNNs) explained

https://www.youtube.com/watch?v=FmpDIaiMIeA

How Convolutional Neural Networks work


https://www.analyticsvidhya.com/blog/2021/05/convolutional-neural-networks-cnn/


Introduction to Convolutional Neural Networks (CNN)

https://bdtechtalks.com/2020/01/06/convolutional-neural-networks-cnn-convnets/

What are convolutional neural networks (CNN)?