A sophisticated deep learning model using Keras to accurately classify between images of dogs and cats.
Trained the model on an extensive dataset comprising 25,000 images of cats and dogs, achieving an impressive accuracy rate of approximately 99%, ensuring robust performance and reliable predictions.
Utilized a comprehensive suite of libraries including TensorFlow, Keras, Numpy, and openCV, leveraging their powerful functionalities to streamline model development and optimization processes.
Curated and utilized high-quality datasets sourced from reputable platforms such as Kaggle, ensuring the integrity and diversity of the training data to enhance the model's generalization capabilities.
Deployed the project on the Hugging Face platform, providing a centralized and accessible location for users to explore the model's architecture, performance metrics, and inference capabilities, fostering collaboration and knowledge sharing within the AI community.
DataSets used : https://www.kaggle.com/competitions/dogs-vs-cats/data
Project Live On : https://huggingface.co/spaces/Vignesh455/Cat-Dog