This project implements a Convolutional Neural Network (CNN) for image classification using the CIFAR-10 dataset. The goal is to train a deep learning model to accurately classify images into 10 different classes.

• src/: Contains the source code for the CNN implementation.

  • cnn_model.py: Python script defining the CNN architecture.
  • train.py: Python script for training the CNN model on the CIFAR-10 dataset.
  • evaluate.py: Python script for evaluating the trained model on test data.

• notebooks/: Jupyter Notebooks for exploration and analysis.

  • Data_Exploration.ipynb: Notebook exploring the CIFAR-10 dataset.
  • Model_Training.ipynb: Notebook containing the model training process.

• data/: Placeholder for the CIFAR-10 dataset. Use the https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz dataset

• Python 3.x
• TensorFlow
• Matplotlib
• NumPy

1. Clone the repository:

   git clone https://github.com/yourusername/cnn-image-classification.git
   cd cnn-image-classification