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Implement Convolutional Neural Network #55

@iamakashrout

Description

@iamakashrout

📌 Description
Implement a Convolutional Neural Network (CNN) for image classification on a well-known dataset (e.g., CIFAR-10, MNIST, or any publicly available dataset). This task will involve:

  • Loading and preprocessing the image dataset
  • Performing exploratory data analysis (EDA) to understand class distribution
  • Building and training a CNN using TensorFlow/Keras or PyTorch
  • Evaluating model performance using accuracy, confusion matrix, and other metrics
  • Visualizing model predictions and feature maps

🎯 Goals

  • Understand and implement image classification using deep learning
  • Work with real-world image data
  • Learn how to optimize and fine-tune CNN models

🛠 Tech Stack

  • Python
  • pandas, numpy, matplotlib/seaborn for data handling & visualization
  • TensorFlow/Keras or PyTorch for deep learning

📖 Resources

How to Contribute

  1. Comment on this issue to get assigned
  2. Fork the repository and create a new branch
  3. Implement the solution and test it
  4. Create a pull request linking this issue

Looking forward to your contributions! 🚀

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