KNN algorithm from scratch for cat vs dog image classification using Python. Machine learning, distance-based classification, and computer vision experiment.

Image classification for dogs and cats with VGG-16 using PyTorch. Model accuracy: 99.6%. Classification API included

A CNN to distinguish between cat images and dog images with a fairly high accuracy with less data

A deep learning project built with PyTorch and deployed using Streamlit to classify images as either a cat or a dog.

An exploration of the trade-off between image quality and accuracy.

a simple CNN to classify a binary class consist of dogs and cats powered by TensorFlow.keras

Image classifier for cats vs dogs using MobileNetV2 and TensorFlow/Keras

This Repository contain algorithm to classify whether images contain either a dog or a cat. This is easy for humans, dogs, and cats. But computer will find it a bit more difficult.

Deep learning model for Cats vs Dogs competition in Kaggle. Also it contains CNN's filters and feature maps visualizations.

A convolutional neural network (CNN)-based image classification project developed as part of the FreeCodeCamp Machine Learning with Python certification. The model is trained to distinguish between images of cats and dogs using TensorFlow/Keras.

A simple classifier model that fine-tune the InceptionV3 model

🐾 Explore K-Nearest Neighbors for cat vs dog image classification, diving into data transformation and geometric decision-making for educational insights.