README.md

Animal Classification Using Convolutional Neural Network

This project aims to classify animals into 5 different classes and One vs rest classifier using a Convolutional Neural Network (CNN). The dataset consists of images of different set of animals.

• 5-Class.ipynb : 5-class classification
  
• Ovr-3-fold.ipynb : One vs rest classififcation
  I have only taken 15 classes of animals for training
  
• Folders '5 classes of animals' and '15 classes of animals' are the respective image dataset used for building this CNN models

Resources used

1. Kaggle notebooks : Referred notebooks of kaggle master's who implement transfer learning techniquesm like EfficientNetB3.
2. Stackoverflow : Articles related to One vs rest to get the concept clarity and also used to resolve errors in the code.
3. Medium Blogs : Articles to gain practical ways of implementing CNN.
4. Tensorflow and Keras Documentation : Referred it for code syntax and execution.
5. Youtube : Codebasics channel for studying concepts of CNN like padding, stride, Flatten , Dropout etc.
6. ChatGPT : Used for resolving error.