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Added Project: Image Classification Using CNN (CIFAR-10 Dataset) under the Neural Networks Folder #823

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Nov 8, 2024
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Added Project: Image Classification Using CNN (CIFAR-10 Dataset) under the Neural Networks Folder #823

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1,064 changes: 1,064 additions & 0 deletions ...Image Classification Using CNN (CIFAR-10)/Image_Classification_Using_CNN_(CIFAR_10).ipynb
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# Image Classification Using Convolution Neural Networks

<img width="659" alt="1" src="https://github.com/sanyadureja/-Image-Classification-using-Convolution-Neural-Networks-CNNs-/assets/84080312/a48be9bf-2e29-41e8-8597-394735df1092">

<img width="658" alt="2" src="https://github.com/sanyadureja/-Image-Classification-using-Convolution-Neural-Networks-CNNs-/assets/84080312/7ca3f7a0-7768-4440-b219-17eee1bfd8a2">

<img width="658" alt="3" src="https://github.com/sanyadureja/-Image-Classification-using-Convolution-Neural-Networks-CNNs-/assets/84080312/a387b507-69f3-46a8-b6c1-08d063c0e9b0">

## Project Structure
- `Image_Classification_Using_CNN_(CIFAR_10).ipynb`- Contains the .ipynb file (Jupyter notebook).
- `Model_Prediction.sav` - Contains model saved using Pickle which can be deployed in production environments where it will serve predictions based on incoming data. The Pickle format makes it easy to integrate with various frameworks, such as Flask, Django, or FastAPI.

## How to Run
1. Clone the repository.
2. Run the `.ipynb` notebook.
3. The Model_Prediction.sav will be saved.




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