This repository contains code and blog on how to build a Image Classifier on Wild Animal Dataset in python. In this project, I have experimented with various machine learning and Deep learning Algorithms and compared their performance.
The Dataset can be downloaded from Kaggle by clicking here. You need a Kaggle account to download the dataset. The dataset contains wild animal images of 6 different species. Download them into a directory named wild_animals_images in the current directory.
Install required dependencies using the following command:
pip install -r requirements.txt
code is in the form of jupyter notebook. You can run the notebook using the following command:
jupyter notebook
It will open the jupyter notebook in your browser. You can run the code cells in the notebook.
All the visualizations will be saved into a directory called visualizations in the current directory.
Trained Models will be saved into a directory called models in the current directory.
You can read the blog on this project here.
For any queries, feel free to open an issue.