Deep Learning Projects Repository

Welcome to the Deep Learning Projects Repository! This repository contains multiple deep learning projects covering natural language processing (NLP), computer vision, audio processing, and object detection using TensorFlow/Keras and PyTorch.

Table of Contents

• Introduction
• Projects
• Installation
• Usage
• Dataset Sources
• Contributing

Introduction

This repository contains various deep learning applications, including text classification, image classification, object detection, and audio processing. Each project includes a Python implementation, dataset usage, and model training/evaluation.

Projects

1. Fake News Detection (NLP - LSTM)

• Task: Classify news articles as real or fake using LSTMs.
• Tech Stack: TensorFlow/Keras, NLP, LSTM.
• Dataset: Fake News dataset (CSV format with text and labels).

2. Image-Based Disease Diagnosis (CNN for X-ray Classification)

• Task: Classify chest X-ray images as normal or pneumonia.
• Tech Stack: TensorFlow/Keras, CNN, Image Processing.
• Dataset: Chest X-ray dataset (image dataset with binary classification).

3. Handwritten Digit Recognition (CNN for MNIST)

• Task: Recognize digits (0-9) from the MNIST dataset.
• Tech Stack: TensorFlow/Keras, CNN.
• Dataset: MNIST (28x28 grayscale images).

4. Music Genre Classification (CNN for Spectrograms)

• Task: Classify music files into different genres.
• Tech Stack: TensorFlow/Keras, CNN, Spectrogram Processing.
• Dataset: GTZAN music dataset (spectrogram images).

5. Object Detection for Autonomous Driving (YOLOv5)

• Task: Detect objects in images/videos using YOLOv5.
• Tech Stack: PyTorch, YOLOv5.
• Dataset: COCO dataset / Custom dataset.

Installation

Prerequisites

Ensure you have the following installed:

• Python 3.8+
• TensorFlow/Keras
• PyTorch (for YOLOv5)
• OpenCV, Pandas, NumPy

Setup

Clone the repository:

$ git clone https://github.com/your-username/deep-learning-projects.git
$ cd deep-learning-projects

Install required dependencies:

$ pip install -r requirements.txt

Usage

Each project is in its respective folder. Navigate to the folder and run the script.

Example (Run Fake News Detection):

$ cd fake-news-detection
$ python fake_news_classifier.py

Dataset Sources

• Fake News Dataset: Kaggle
• Chest X-ray Dataset: NIH Dataset
• MNIST Handwritten Digits: TensorFlow Dataset
• GTZAN Music Dataset: Marsyas
• COCO Dataset for Object Detection: COCO

Contributing

Contributions are welcome! Feel free to fork the repository and submit a pull request.

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Happy Coding! 🚀