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How does convolution works? Watch this live convolution demo in python
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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:
▬▬▬▬▬▬ ⏰ 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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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
- 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:
▬▬▬▬▬▬ ⏰ 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:
------------------
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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