CIFAR-10 Image Classification using Neural Network

This assignment demonstrates an image classification task on the CIFAR-10 dataset using a simple Neural Network implemented with TensorFlow/Keras.

Dataset

The CIFAR-10 dataset consists of 60,000 32x32 color images in 10 classes, with 6,000 images per class.

Prerequisites

• Python 3.x
• TensorFlow (version >= 2.x)
• Matplotlib
• Numpy

Installation

1. Clone this repository:

   git clone https://github.com/pyritez3/DL-Simple-NN.git
   
   cd DL-Simple-NN
   

2. Install the required libraries:

   pip install tensorflow matplotlib numpy

Results

The model is trained on the CIFAR-10 dataset for 100 epochs. The training and test accuracy and loss graphs are shown in the "MODEL ACCURACY" and "MODEL LOSS" plots.

License

This project is licensed under the MIT License