Deep-Learning

Deep Learning Projects Repository

This repository contains a collection of deep learning projects exploring various applications and techniques. Each project is organized into a dedicated folder with its own detailed README file, datasets, and implementation.

Projects Included

1. Food Image Classification (Food-101 Dataset):

   • A project to classify food images into 101 categories using Convolutional Neural Networks (CNNs) and PyTorch.
   • Details in the project folder

2. Image Segmentation Project: -A project to annotate and segment images using deep leaning tools.

Key Objectives

• Explore the use of deep learning models for solving diverse real-world problems.
• Experiment with various neural network architectures, optimizers, and techniques.
• Provide structured code, detailed documentation, and reproducible results for each project.

Structure

The repository is organized as follows: Deep-Learning/ ├── Food-Image-Classification/ │ ├── Food-101_Dataset/ │ ├── Model_Training.ipynb │ ├── README.md ├── [Another Project Folder]/ │ ├── ... └── README.md

Tools and Frameworks

• Python
• PyTorch
• TensorFlow (if applicable)
• Jupyter Notebooks

How to Use

1. Clone the repository:

   git clone https://github.com/your-username/Deep-Learning.git