Simple explanation of convolutional neural network | Deep Learning Tutorial 23 (Tensorflow & Python)
A very simple explanation of convolutional neural network or CNN or ConvNet such that even a high school student can understand it easily. This video involves very less math and is perfect for total beginner who doesn't have any idea on what CNN is and how it works. We will cover different topics such as,
1. Why traditionally humans are better at image recognition than computers?
2. Disadvantages of using traditional artificial neural network (ANN) for image classification.
3. How human brain recognizes images?
4. How computers can use filters for feature detection
5. What is convolution operation and how it works
6. Importance of ReLU activation in CNN
7. Importance of pooling operation in CNN
8. How to handle rotation and scale in CNN
🔖 Hashtags 🔖
#convolutionalneuralnetwork #cnndeeplearning #cnntutorial #cnnmachinelearning #cnnalgorithm #cnnpython #cnntensorflow
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Here are some good articles on CNN,
Is CNN scale/rotation invariant?
https://stats.stackexchange.com/questions/239076/about-cnn-kernels-and-scale-rotation-invariance#:~:text=22-,1)%20The%20features%20extracted%20using%20CNN%20are%20scale%20and%20rotation,details%2C%20see%3A%20Deep%20Learning.&text=Convolution%20is%20not%20naturally%20equivariant,or%20rotation%20of%20an%20image.
https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/
PDF Paper on cnn: http://www.deeplearningbook.org/contents/convnets.html
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Need help building software or data analytics and AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website.
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DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.
A very simple explanation of convolutional neural network or CNN or ConvNet such that even a high school student can understand it easily. This video involves very less math and is perfect for total beginner who doesn’t have any idea on what CNN is and how it works. We will cover different topics such as,
1. Why traditionally humans are better at image recognition than computers?
2. Disadvantages of using traditional artificial neural network (ANN) for image classification.
3. How human brain recognizes images?
4. How computers can use filters for feature detection
5. What is convolution operation and how it works
6. Importance of ReLU activation in CNN
7. Importance of pooling operation in CNN
8. How to handle rotation and scale in CNN
🔖 Hashtags 🔖
#convolutionalneuralnetwork #cnndeeplearning #cnntutorial #cnnmachinelearning #cnnalgorithm #cnnpython #cnntensorflow
Do you want to learn technology from me? Check https://codebasics.io/ for my affordable video courses.
🤝 Support my youtube channel by buying a data science, coding 👕 T-shirt: https://kaaipo.com/collections/coding-collection/?utm_source=youtube&utm_medium=post&utm_campaign=codebasics-community
Deep learning playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO
Machine learning playlist : https://www.youtube.com/playlist?list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw
Here are some good articles on CNN,
Is CNN scale/rotation invariant?
https://stats.stackexchange.com/questions/239076/about-cnn-kernels-and-scale-rotation-invariance#:~:text=22-,1)%20The%20features%20extracted%20using%20CNN%20are%20scale%20and%20rotation,details%2C%20see%3A%20Deep%20Learning.&text=Convolution%20is%20not%20naturally%20equivariant,or%20rotation%20of%20an%20image.
https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/
PDF Paper on cnn: http://www.deeplearningbook.org/contents/convnets.html
🌎 My Website For Video Courses: https://codebasics.io/
Need help building software or data analytics and AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website.
Discord: https://discord.gg/r42Kbuk
Website: https://codebasics.io/
Facebook: https://www.facebook.com/codebasicshub
Twitter: https://twitter.com/codebasicshub
Linkedin: https://www.linkedin.com/company/codebasics/
DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers’.
