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CNN with MNIST Turkish

In this project, we have used a Convolutional Neural Network (CNN) to recognize handwritten digits from the MNIST dataset. This dataset is widely used for training various image processing systems.

CNN Architecture

türkçe olarak cnn modelini mnist ile güzel bir şekilde anlatmaya çalıştım umarım beğenirsini :) (kısaca)

Overview

  • Objective: Build a CNN model to accurately classify handwritten digits in Turkish.
  • Dataset: The MNIST dataset contains 60,000 training images and 10,000 testing images of handwritten digits.
  • Model Architecture: The CNN architecture includes multiple convolutional layers, pooling layers, and fully connected layers to enhance the feature extraction process.
  • Results: The model achieved high accuracy, demonstrating the effectiveness of CNNs in image classification tasks.

Installation

To run this project, you will need the following libraries:

  • TensorFlow
  • Keras
  • NumPy
  • Matplotlib
  • OpenCV

Usage

  1. Clone the repository: 
    git clone https://github.com/yourusername/CNN_with_MNIST_Turkish.git