This project is part of the FreeCodeCamp curriculum and focuses on training a convolutional neural network model to classify images of cats and dogs.
The project utilizes TensorFlow and the Keras API to build and train the model. It includes data preprocessing, model training, evaluation, and testing.
The dataset used in this project consists of images of cats and dogs. The dataset can be obtained from the FreeCodeCamp project data repository.
cat_dog_script.py: Contains the main code for training and evaluating the model.Copy_of_fcc_cat_dog.ipynb: A modified version of the original Google Colab notebook used for data preprocessing and model training.README.md: The file you are currently reading, providing information about the project.
- Clone the repository.
- Download the dataset using the provided link in the code.
- Run
cat_dog_script.pyto train, evaluate, and test the model. - Check the model's accuracy in identifying cats and dogs images.
After training the model, it is tested on a set of images. The model's accuracy is calculated, aiming for a minimum of 63% accuracy to pass the challenge.
Completed by Anguilet Joan-Yves Darys as part of the FreeCodeCamp curriculum.