This project is an image classification project using a deep-learning based on Convolutional Neural Networks (CNNs) with Keras. The Dogs vs. Cats is a classic problem for anyone who wants to dive deeper into deep-learning.

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.

This repository contains a Convolutional Neural Network (CNN) built with TensorFlow and Keras for binary image classification. The model is trained and evaluated on the Kaggle "Dogs vs. Cats" dataset, demonstrating a complete computer vision workflow from data preprocessing to prediction

To start your Deep Learning Journey with Python, Cats vs Dog classification is the best fundamental Deep Learning project. In this project, we will create a model with the help of Python keras which will classify whether the image is of dog or cat. About Cats and Dogs Prediction Project In this project, we will be using a Convolutional Neural Network to create our model which will predict whether the image is of dog or cat. We will create a GUI in which we will directly upload the image and predict whether the image contains a dog or cat. Now, let’s directly dive into the implementation of this project: Dataset we will be using: In this we will be using the famous dataset that is the Asirra( animal species image recognition for restricting access) dataset, which was introduced in 2013 for a machine learning competition. The dataset consist of 25,000 images with equal numbers of cats and dogs. You can download the Dogs and Cats dataset using the following link: Dogs and Cats Dataset Project Prerequisites: You should firstly install all the required libraries in your system with the help of pip installer. The name of libraries you should install are: Numpy Pandas Matplotlib Tensorflow Keras sklearn You can install this using pip by opening your cmd and type (For ex: pip install numpy, pip install tensorflow, pip install pandas, etc).

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.

Cats vs Dogs Image Classification Project with Tensorflow Deep Learning (Convolutional Neural Network)

A binary Image Classifier for Cats-vs-Dogs classification using Convolutional Neural networks with Data Augmentation in Python.

This repository contains an ipython notebook which implements a Convolutional Neural Network to do a binary image classification. I used this to classify Cats vs Dogs and you can get the dataset from here https://www.kaggle.com/c/dogs-vs-cats/data . (This model trains with thousands of input images so be patient.)

Cats vs. Dogs Image Classification using Convolutional Neural Networks with Keras

Cats vs. Dogs Image Classification with Convolutional Neural Network on GPU

Dogs vs. Cats: Image Classification with Deep Learning using Convolutional Neural Networks (CNN)

Image classification using Convolutional Neural Networks (CNN) with TensorFlow. Model trained on Cats vs Dogs dataset.

A Convolutional Neural Networks (CNN) deep learning model built with PyTorch and PyTorch Lightning for Cats vs. Dogs image classification.

Convolutional Neural Network (TensorFlow/Keras) for binary image classification of cats vs dogs. Includes data preprocessing with augmentation, training notebook, and single-image prediction examples.

A deep learning project for classifying images of cats and dogs. Built using CNNs (Convolutional Neural Networks) with TensorFlow/Keras. Trained on the Cats vs Dogs dataset to achieve high image classification accuracy. Demonstrates computer vision and image recognition fundamentals.

# Cats vs Dogs Classification 🐱🐶 A Convolutional Neural Network (CNN) built with TensorFlow/Keras to classify images of cats and dogs using the `cats_vs_dogs` dataset from TensorFlow Datasets. --- ## 📦 Requirements - Python 3.8+ - TensorFlow - TensorFlow Datasets Install dependencies: ```bash pip install -r requirements.txt

🚀 Just completed a deep learning project on Image Classification: Cats vs Dogs using Convolutional Neural Networks (CNN) in Keras! 🖼️ Built a custom CNN model with multiple layers to accurately distinguish between cats and dogs based on image features.

A Deep Learning project that classifies images of cats and dogs using a Convolutional Neural Network (CNN) built with TensorFlow and Keras. The model is trained on the TensorFlow Datasets (TFDS) Cats vs Dogs dataset and achieves binary image classification.

This repository contains a Deep Learning project focused on binary image classification using the famous Kaggle Dogs vs. Cats dataset. The goal is to build and train a Convolutional Neural Network (CNN) to distinguish between images of cats and dogs with high accuracy.

Dog vs Cat Image Classification using CNN is a deep learning project that classifies images of dogs and cats using a Convolutional Neural Network built with TensorFlow and Keras. The model learns visual features from images and achieves accurate binary classification.

Image classification model built with TensorFlow and Keras to distinguish cats vs dogs using deep learning and computer vision techniques. The model employs a convolutional neural network (CNN) architecture and is trained on the Dogs vs Cats dataset. This implementation serves as an end-to-end tutorial for applying dl to image classification.

Cat vs Dog Image Classification using CNN | Deep Learning Project This project classifies images of cats and dogs using a Convolutional Neural Network (CNN). The model achieves high accuracy with data augmentation, regularization, and transfer learning techniques.

In this Cat VS Dog image classification project, I used Convolutional Neural Networks (CNNs) for image binary classification to distinguish between dogs and cats. Built with deep learning frameworks like TensorFlow and Keras, it showcases techniques in image processing and applying CNNs to binary classification problems.

CatDogDetector is a Python-based machine learning project that uses a convolutional neural network (CNN) to classify images as cats or dogs with ~90% accuracy. Trained on the Kaggle Cats vs Dogs dataset, it’s ideal for beginners learning image classification or developers building pet-related apps.

A modular Convolutional Neural Network (CNN) built with TensorFlow/Keras for binary image classification (cats vs. dogs). Includes a training notebook, sample dataset, performance plots, and a clean project structure for reproducibility and collaboration.

Built a Convolutional Neural Network (CNN) with TensorFlow and Keras for binary image classification (cats vs. dogs). Used ImageDataGenerator for data augmentation to prevent overfitting. The model, with convolutional, max-pooling, and dense layers, was trained, saved, and demonstrated successful inference on new images

🐶🐱 Dog vs. Cat Classification using CNN A deep learning project utilizing Convolutional Neural Networks (CNN) with TensorFlow & Keras to classify images of dogs and cats. The model includes data preprocessing, regularization techniques, and performance visualization. 🚀

A deep learning-based project that classifies images as cats or dogs using a Convolutional Neural Network (CNN). Built and trained in Google Colab using the Kaggle Dogs vs Cats dataset, this notebook allows users to upload or capture images and get real-time predictions. Ideal for beginners exploring image classification with TensorFlow.

The Dog vs Cat Classification project uses deep learning to classify images as either dogs or cats. It involves preparing a labeled dataset, preprocessing images (resizing, normalization, augmentation), and training a Convolutional Neural Network (CNN) or using transfer learning with pre-trained models.

This project is an image classification project using a deep-learning based on Convolutional Neural Networks (CNNs) with Keras. The Dogs vs. Cats is a classic problem for anyone who wants to dive deeper into deep-learning.