Add CNN Architecture and Training Process Tutorial

[Mukta64Chaudhari]

This PR adds a new tutorial on Convolutional Neural Networks (CNN), covering both the architecture and training process.

Key Changes:

• Added Architecture_Of_CNN.md in the Tutorials folder.
• Detailed explanation of the CNN architecture, including:
• Input Layer
• Convolutional Layers
• Activation Functions (ReLU)
• Pooling Layers
• Fully Connected Layers
• Output Layer
• Outlined the training process for CNNs, including:
• Forward Propagation
• Loss Calculation
• Backpropagation
• Weight Update
• Regularization Techniques
• Purpose

This tutorial aims to provide a comprehensive understanding of how CNNs work and how to train them effectively, catering to both beginners and those looking to refresh their knowledge in deep learning.

Please review and consider merging this addition to enhance the repository's educational resources.