A friendly introduction to Convolutional Neural Networks (CNN) & Image Recognition explained| NerdML

In this video, we explain the concept of Convolutional Neural Networks, how they're used, and how they work on a technical level. We also discuss the details behind convolutional layers and filters.
A friendly explanation of how computer recognize images, based on Convolutional Neural Networks.
All the math required is knowing how to add and subtract 1's. (Bonus if you know calculus, but not needed.)

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Timeline:
Start ( 0:00 )
1).​ What is Convolutional Neural Network? ( 0:31 )
2). Explanation about Convolutional + ReLU ( 4:07 )
3). Explanation about Pooling Layer ( 8:17 )
4). Explanation about Fully Connected Layer ( 10:51 )
5). Convolutional Neural Network Applications ( 12:35 )

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For a brush up on Neural Networks, check out this video:    • Neural Network In 5 Minutes | What is a Ne...  

A Convolutional Neural Network (ConvNet/CNN) is a Deep Learning algorithm which can take in an input image, assign importance (learnable weights and biases) to various aspects/objects in the image and be able to differentiate one from the other. The pre-processing required in a ConvNet is much lower as compared to other classification algorithms. While in primitive methods filters are hand-engineered, with enough training, ConvNets have the ability to learn these filters/characteristics.

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Please find the previous Video link -
Vanishing/Exploding Gradients - An Old Problem resulting from backpropagation (Deep Learning SIMPLIFIED) | NerdML :    • Vanishing/Exploding Gradients - An Old Pro...  

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