How does convolution works? Watch this live convolution demo in python
With the help of small python code snippet and different kernel or filters, this small video is all you need to understand how to convolution works in CNN. I will walk line by line the Python code code snippet to show you:
How the source image is read?
How the empty target image is created based on source and kernel?
How to source image region is selected and read?
How does kernel is applied on source image region as matrix multiplication?
How does the final convolution value is generated?
How the target image gets all its value?
You will see both the source and target image after the convolution?
You will also learn which kernel or the filter works better and which does not?
GitHub resource for this workshop:
https://github.com/prodramp/DeepWorks...
▬▬▬▬▬▬ ⏰ TUTORIAL TIME STAMPS ⏰ ▬▬▬▬▬▬
(00:00) Quick Introduction
(01:30) Google colab notebook intro
(02:18) CNN Explainer Intro
(05:15) Convolution Demo Starts
(05:50) Various Kernel or Filters
(06:30) Source image as Input
(07:05) Convolution code starts
(08:15) Output image rows and cols
(10:30) First Kernel runs and feature map
(10:45) Second Kernel runs and feature map
(11:10) Third Kernel runs and feature map
(11:35) Fourth Kernel runs and feature map
(12:00) Fifth Kernel runs and feature map
(12:50) Notebook push at GitHub
Please visit:
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Prodramp LLC | https://prodramp.com | @prodramp
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Content Creator: Avkash Chauhan (@avkashchauhan)
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Tags:
#python #pytorch #ml #ai #aicloud #h2oai #driverlessai #machinelearning #cloud #mlops #model #collaboration #deeplearning #modelserving #modeldeployment #keras #tensorflow #pytorch #datarobot #datahub #aiplatform #aicloud #modelperformance #modelfit #modeleffect #modelimpact #modelbias #modeldeployment #modelregistery #modelpipeline #neptuneai #streamlit #pythonapps #deepchecks #modeltesting #codeartifact #dataartifact #modelartifact #onnx #aws #supervisor #supervisord #kaggle #keplergl #mapbox #lightgbm #xgboost #classification #regression #dataengineering #pandas #keras #tensorflow #tensorboard #mnist #cnn #convnet #alexnet #prodramp #avkashchauhan #cnnexplainer #gnn #graph #graphneuralnetwork #pyg #networkx
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