Convolutional Neural Networks | CNN | Kernel | Stride | Padding | Pooling | Explained by Python Code

Explained all important building block of Convolutional Neural Networks through Keras Python code.
What is the actual building blocks like Kernel, Stride, Padding, Pooling, Flatten?
How these building blocks are help to reduce dimensionality with keeping all important feature.
What is the formula to get output layer dimension?
Convolutional Neural Networks | CNN | Kernel | Stride | Padding | Pooling | Flatten | Formula • Convolutional Neural N...
Neural Networks - Feedforward Algorithm | Matrix Math behind | Forward Propagation in a Deep Network. • Neural Networks - Feed...
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[@srinivb1]

Awesome video on CNN numericals. Thanks Binod for this video.

[@binodsuman]

Thank you so much Srini. Good to know this CNN Tutorial video somehow helped you for your learning.

[@uthamasrinivas3333]

Thank you sir, your explaination of the concept is very good sir. 👍

[@VersatileAnthem]

thanks for to the point explanation.

[@dr.junaidslectures583]

What a great explanation. Thank you so much

[@pradeepsingh-zu1pi]

Thanks for your videos, could you please provide link for CNN fully connected layer functionality after dimension reduction. I can not able to find it in your library

[@kaushalkumar3017]

best for initial hands-on Convolution NN and understanding its terminologies.

[@binodsuman]

Thank you Kaushal. Nice to hear that Convolutional Neural Network CNN all basic concept building blocks video helped you to learn. Keep Learning !!

[@sandeepar6342]

nice hands-on tutorials

[@binodsuman]

Thanks Sandeep. Happy to see this Convolutional Neural Network Basic concept by python code helped you. Keep Learning !!

[@sumalatha3575]

Great explanation thank you very much sir

[@binodsuman]

Happy to hear Suma, this CNN and related concept videos Tutorial series helped you. Keep Learning !! @binodsumanacademy

[@thecityofknowledge]

Hello sir, could you please share the link of the code? I couldn't execute the code.thanks

[@sophiez7952]

thanks, if I have a matrix is 15 * 21 *1 ,which means 15 rows ,21 columns, channel=1, so the height !=width, can I still apply can, how can I do ? thanks!

[@ganeshsubramanian6217]

Absolutely loved this, thank you!
Please continue to make more videos sir.

[@venugopalt6861]

Thank you so much binod for a great tutorial onCNN

[@Abolhesh3354]

Thank you very much.. well explained!! Can I use numerical continuous data instead of images to build a regression CNN model and how? Thanks.

[@jpbs4281]

Very nicely explained!

[@gabrielasarama]

Great explained, thank you!

[@saulesha123]

great explanation! thank you!

[@srinivaskedarisetty3437]

Superb... You made it pretty easy

[@lucky_technical8557]

excellent presentation sir

[@sophiez7952]

how can I apply CNN if the height and width is not equal ,thanks

[@srinivasrathodkethavath9545]

Very clearly explained. Thanks

[@yadneshgulhane1051]

Thanks for the video sir, the explanation is nice. Could you please explain YOLOv3 with code for custom datasets

[@akshitha2410]

Sir is it possible to find the displacement(location of max value) in max pooling?

[@hemantvardani1436]

thank for this video

[@srinivb1]

Binod, can you please share the ipynb file used in this video ? Thanks

[@binodsuman]

Glad to hear, this CNN building block video helped you to learn. Here is the link for ipynb github.com/binodsuman/deep-learning/blob/master/CNN_Kernel_Stride_Padding_Pooling.ipynb

[@alaaahmed3733]

Can you explain the Flatten please

[@bharath5673__]

really helpful

[@binodsuman]

Thank you so much for your kind words! I'm glad to hear that you found it informative and I appreciate your feedback. It motivates me to keep creating more content. Thanks again for your support!

[@wahabkhan-ug4ri]

where is the input image??

[@toshyamg]

👏👏👏

[@vinayakganji5067]

Hi Binod, Could you please share the ipynb file

[@binodsuman]

Happy to know this CNN building block video helped you. Here is the link for ipynb github.com/binodsuman/deep-learning/blob/master/CNN_Kernel_Stride_Padding_Pooling.ipynb

[@vinayakganji5067]

@@binodsuman Many thanks for sharing ipynb file.

[@kidstalento7141]

@@binodsuman pls send this images file

[@muhammadqasim8776]

please share ipynb file

[@luiscao7241]

those who do not basically understand CNN's work after seeing this video should not pursue their career on ML. :))

[@ajaystyles8369]

😂😂😂 my first time watching a CNN video, seems like I got lucky… I understand all the concept flawlessly

[@thegadgetfusion1138]

sir aap bahut bekaar padha rahe ho. because aap paper pass to kara doge lekin aap application point of view se nahi samjha rahe ho.
actually matlab kya hai pooling padding ka why we use in deep learning..
plz cheezon ko clear kijiye achhe se ... that is it