reza-debug / cnn_projects

CNN_Project

Fashion MNIST Pictures

Overview

This Jupyter notebook provides a step-by-step guide to building a CNN model to classify fashion items from the Fashion MNIST dataset. The Fashion MNIST dataset consists of 60,000 training images and 10,000 test images of 10 different fashion items, such as t-shirts, trousers, and shoes.

Instructions

To follow along with this notebook, you will need to have the following installed:

Python TensorFlow or PyTorch A GPU (optional)

Once you have the required dependencies installed, you can clone the repository and open the Fashion_mnist_pictures.ipynb notebook in a Jupyter environment.

following topics:

Importing the necessary libraries

Loading the Fashion MNIST dataset

Preprocessing the data

Building the CNN model

Training the CNN model

Evaluating the CNN model

Visualizing the results

Conclusion

This Jupyter notebook provides a practical introduction to building CNN models for image classification tasks. By following along with this notebook, you will learn how to build a CNN model that can accurately classify fashion items from the Fashion MNIST dataset.

Resources

The following resources may be helpful for learning more about CNNs and the Fashion MNIST dataset:

Convolutional Neural Networks (CNNs): https://www.tensorflow.org/tutorials/images/cnn: https://www.tensorflow.org/tutorials/images/cnn

Fashion MNIST Dataset: https://github.com/zalandoresearch/fashion-mnist: https://github.com/zalandoresearch/fashion-mnist

TensorFlow: https://www.tensorflow.org/: https://www.tensorflow.org/

PyTorch: https://pytorch.org/: https://pytorch.org/

I hope you find this notebook helpful for learning about CNNs and image classification.

Feel free to connect with me on LinkedIn: [www.linkedin.com/in/reza-abdolahi0175]

Thank you!