1. Image Classification-Caltech101 dataset

Image Classification with Caltech 101 Dataset

This folder contains code for a project that uses the Caltech 101 dataset to train a deep learning model for image classification.

Dataset:

The Caltech 101 dataset is a collection of images of objects belonging to 101 different categories. The dataset was created by researchers at the California Institute of Technology and is widely used for testing image classification algorithms. Download the dataset from here or here.

Project Goal:

The goal of this project is to train a deep learning model that can accurately classify images from the Caltech 101 dataset into their respective categories.

Experimenting with various hyperparameters like

1. Network Topology
2. Number of layers
3. Shape of conv2d layer

Document in the form of a blog post explaining the project and the results.

Usage:

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.

Blog:

The blog post for this project can be found here.

Code:

The code for this project can be found here.