This project implements a Dog vs Cat classifier using deep learning techniques. It utilizes convolutional neural networks (CNNs) to accurately classify images of dogs and cats. Built with Python and TensorFlow, this model can be trained on a dataset of labeled images to distinguish between the two animals, enabling efficient image classification.

Deep learning project that classifies images of cats and dogs using Convolutional Neural Networks (CNN). Includes image augmentation, model training, and evaluation using TensorFlow

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CNN Image Classifier Python project using TensorFlow/Keras to classify cat vs. dog images. Features GUI, TensorBoard, and model persistence.

This repository contains a Python script for building a Convolutional Neural Network (CNN) using TensorFlow and Keras to classify images of cats and dogs. The model is trained on the Dogs vs. Cats dataset and can predict whether an input image is a cat or a dog.

✅ Project Title: Dog vs Cat Image Classification using CNN 📌 Tools Used: Python, TensorFlow, Keras, CNN, Jupyter Notebook, PIL 🧠 Overview: Built a Convolutional Neural Network (CNN) model to classify images of dogs and cats.

🐱🐶 Built a deep learning model to classify Cat vs Dog images using TensorFlow & Streamlit. Upload an image and get instant predictions in your browser. 🔗 [Run with Streamlit] 💻 CNN | Python | Keras | Streamlit 📂 Model: cat_dog_classifier_model.h5