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CNNs have become fundamental in computer vision and image analysis. They are behind cutting-edge technologies like image recognition, object detection, and more. Learning CNNs can open up exciting career opportunities and enable you to create innovative applications.

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RaphaelGN/Image-classification-CNN-Deep-Learning

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Why Learn CNNs?

CNNs have become fundamental in computer vision and image analysis. They are behind cutting-edge technologies like image recognition, object detection, and more. Learning CNNs can open up exciting career opportunities and enable you to create innovative applications.

Créer un environement CONDA et installer les requirements

conda create --name $ENVIRONMENT_NAME python tensorflow --file requirements.txt

conda create --name cnn_raphael python=3.9 --file requirements.txt et ou pip install -r requirements.txt

pour activer l'environement CONDA

conda activate cnn_raphael

pour le deactiver

conda deactivate

Pour créer un docker

docker build -t cnn-docker .

Pour lancer un docker

docker run cnn-docker

dashboard

%load_ext tensorboard %tensorboard --logdir logs

Happy learning! 🚀

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CNNs have become fundamental in computer vision and image analysis. They are behind cutting-edge technologies like image recognition, object detection, and more. Learning CNNs can open up exciting career opportunities and enable you to create innovative applications.

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