Dog and cat image classifier with deep learning

Classifying cat and dog images using Kaggle dataset

A classifier for cat and dog images (Response to Siraj's challenge of the week)

This is a Flask app that can classify images of dog and cat. The underlying model is a CNN trained using Keras framework

Computer Vision Case Study in image recognition to classify an image to a binary class, based on Convolutional Neural Networks (CNN), with TensorFlow and Keras in Python, to identify from an image whether it is an image of a dog or cat. (Includes: Data, Case Study Paper, Code)

Dog vs Cat Classifier is a deep learning model built with TensorFlow to classify images as either dogs or cats. It utilizes a Convolutional Neural Network (CNN) and is trained on the Dog vs Cat dataset from Kaggle. The repository includes training and prediction scripts, allowing users to train the model and classify new images easily. 🚀

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Using TensorFlow, a deep learning model is trained to distinguish between cat and dog faces. The model analyzes image features to accurately classify whether the face belongs to a cat or a dog, demonstrating a practical application of machine learning for image recognition.

We successfully built a deep neural network model by implementing Convolutional Neural Network (CNN) to classify dog and cat images with very high accuracy 97.32 %. In addition, we also built a Flask application so user can upload their images and classify easily.

Classifier for cat and dog images, a response to Siraj's challenge of the week

Classify dog and cats images using PyTorch

Classify dog and cat images of kaggle data

Cat & Dog Classifier is a browser-based machine learning application that classifies uploaded images as either cat or dog using a convolutional neural network. The project demonstrates how deep learning models can be integrated into a modern frontend stack using React, TypeScript, and TensorFlow.js, enabling real-time inference directly in the brow

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.

Create a custom image classification dataset featuring five classes: dog, cow, cat, lamb, and zebra, each with 100 images sourced from the internet or captured using your phone. Develop a classification model to classify these classes with at least 90% accuracy.

Classify images of dogs and cats using TensorFlow 2.0 and Keras to create a convolutional neural network that correctly classifies images of cats and dogs at least 70% of the time.

a simple image recognition tool that classifies whether the image is of a dog or a cat. The idea is to create a simple Cars/Bikes Image classifier and then applying the concepts on a bigger scale.

Deep Learning Image Classification model ,VGG16 implemented from scratch using custom modelling in keras, to classify images of dog and cats among their respective classes..

Cat vs Dog Image Classification using VGG16 A simple deep learning project using TensorFlow and Keras to classify images of cats and dogs. Uses VGG16 pretrained model with image augmentation, training on local GPU, and supports prediction on new images.

Deep learning project for classifying cat vs. dog images, built from scratch as part of my preparation for MSc AI. Includes multiple CNN architectures, training workflows, and final evaluation.

Modeled a Convolutional Neural Network using PyTorch (CUDA) to classify dog and cat images loaded using TorchVision's ImageFolder and also use pre-trained models such as AlexNet, LeNet and evaluated the model using various metrics

This program implements Convolutional Neural Network (CNN) algorithm using Python, allowing users to upload images and determine whether the uploaded image contains a cat or a dog. The program utilizes a pre-trained CNN model to analyze and classify these images. Various tools such as TensorFlow or PyTorch will be used to implement CNN models. With

A deep learning project using a CNN in TensorFlow to classify cat and dog images. The web app, built with Streamlit, supports real-time camera input and batch file uploads. Implements Grad-CAM for model interpretability, displaying heatmaps of the AI's focus areas on a dynamic, modern user interface.

freeCodeCamp Cat and Dog Image Classifier

Predictive Machine Learning Model to predict Cats or Dogs

In this repository, a convolutional neural network was created to solve the problem of recognizing images of dogs and cats.

This is my project for FreeCodeCamp.org about an Image Classifier of Cats and Dogs for the Machine Learning with Python course.

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FCC Machine Learning: Cat and Dog image classifier

classifying dog and cat images using Convolutional neural net.