End To End Deep Learning Project For Classifying Cat vs Dog Images, using PyTorch
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Updated
Jul 22, 2023 - Jupyter Notebook
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End To End Deep Learning Project For Classifying Cat vs Dog Images, using PyTorch
Resnet50 Transfer Learning
My Deep Learning Work
Tensorflow deep learning model serving using flask. The template is simple as main concern is building the web app. Template making quite easy than serving,it shows all the steps needed to linking the model with our web application.
Tflite model implementation in flutter to detect the cats and dogs.
Developing a web app of machine learning model using flask is quite easy. One should have some basic knowledge in web development,not so much but quite a bit. It is just a introductory web app in flask classifying cat vs dog by deep learning model.
Binary classification, SHAP (Explainable Artificial Intelligence), and Grid Search (for tuning hyperparameters) using EfficientNetV2-B0 on Cat VS Dog dataset.
Differentiate Dogs from cats using Tensorflow
I have trained two different CNN models for binary image classification to see which architecture has better accuracy, takes less time in training, how hyperparamters affect training and how many epochs do each of them need. I achieved 96% accuracy on the best model.
Using a convolutional neural network on different datasets.
This is application created with Flutter to classify weather the image which is provided is shows cat or dog.
Cat Dog Classification
This is a project for a CatvsDog classifier using a very limited number of samples
Implementation of Binary image classification using Tensorflow Keras
using MobilNet to classify cats vs dogs with tensorflow
VGG Deep Convolutional Network fine tuned on Cat vs Dog dataset using Transfer Learning. VGG was trained on famous IMAGENET dataset.
This project focuses on building a powerful image classification model to distinguish between cats and dogs using a Convolutional Neural Network (CNN)
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