/AI-Nexus

AI Nexus is a streamlined suite of AI-powered apps built with Streamlit. It includes StyleScan for fashion classification, GlycoTrack for diabetes prediction, DigitSense for digit recognition, IrisWise for iris species identification, ObjexVision for object recognition, and GradeCast for GPA prediction with detailed insights.

Primary LanguageJupyter NotebookMIT LicenseMIT

🤖 AI Nexus - Multi-Purpose AI/ML Hub

AI Nexus is a central repository that brings together a collection of advanced AI and ML applications. These projects span a wide range of use cases, from image classification to predictive healthcare models.


🌐 Project Highlights

  1. 👗 StyleScan - Fashion MNIST Image Classification
  2. 🩺 GlycoTrack - Advanced Diabetes Prediction
  3. 🌸 IrisWise - Iris Species Classification
  4. 🎓 GradeCast - GPA Prediction Model
  5. 🧮 DigitSense - MNIST Handwritten Digit Classifier
  6. 🖼️ ObjexVision - CIFAR-10 Object Recognition

🎨 Project Image Previews

🧮 DigitSense - MNIST Handwritten Digit Classifier

DigitSense Screenshot 1 DigitSense Screenshot 2

🩺 GlycoTrack - Advanced Diabetes Prediction

GlycoTrack Screenshot 1 GlycoTrack Screenshot 2

🎓 GradeCast - GPA Prediction Model

GradeCast Screenshot 1 GradeCast Screenshot 2

🌸 IrisWise - Iris Species Classification

IrisWise Screenshot 1 IrisWise Screenshot 2

🖼️ ObjexVision - CIFAR-10 Object Recognition

ObjexVision Screenshot 1 ObjexVision Screenshot 2

👗 StyleScan - Fashion MNIST Image Classification

StyleScan Screenshot 1 StyleScan Screenshot 2
StyleScan Screenshot 3 StyleScan Screenshot 4

🚀 Quick Links to Live Demos

Project Live Link
👗 StyleScan - Fashion MNIST Image Classification Open in Streamlit
🩺 GlycoTrack - Advanced Diabetes Prediction Open in Streamlit
🧮 DigitSense - MNIST Handwritten Digit Classifier Open in Streamlit
🌸 IrisWise - Iris Species Classification Open in Streamlit
🖼️ ObjexVision - CIFAR-10 Object Recognition Open in Streamlit
🎓 GradeCast - GPA Prediction Model Open in Streamlit

📂 Projects Overview

1. 🩺 GlycoTrack - Advanced Diabetes Prediction

An intuitive app for predicting diabetes based on health metrics like Glucose, Blood Pressure, BMI, etc. It uses various machine learning models (KNN, Random Forest, SVM, etc.) to provide predictions and performance insights.

Features:

  • Real-time diabetes prediction
  • Interactive user interface with animations
  • Supports multiple machine learning models

2. 🌸 IrisWise - Iris Species Classification

Predict the species of Iris flowers based on input features (sepal and petal dimensions) using K-Nearest Neighbors and other machine learning models.

Features:

  • Real-time iris species prediction
  • Dynamic visualizations and tooltips for enhanced user experience

3. 🎓 GradeCast - GPA Prediction Model

Estimate GPA/CGPA based on student performance data, providing an accurate prediction of academic success. Built using regression models.

Features:

  • Input academic scores to predict GPA
  • Simple and user-friendly interface

4. 🧮 DigitSense - MNIST Handwritten Digit Classifier

Identify handwritten digits (0-9) with this accurate, real-time classifier powered by a CNN model.

Features:

  • Recognizes digits from 0-9
  • Instant results with confidence scores

5. 👗 StyleScan - Fashion MNIST Image Classification

Predict the clothing category from grayscale images of fashion items (shirts, shoes, dresses, etc.) using deep learning models.

Features:

  • Classifies 10 categories of fashion items
  • Accurate predictions using CNN architecture

6. 🖼️ ObjexVision - CIFAR-10 Object Recognition

Recognizes 10 types of objects including airplanes, birds, and automobiles using CNNs.

Features:

  • Real-time object recognition
  • 10 object categories with instant prediction feedback

🛠️ Installation & Setup

To set up any of the projects, follow the steps below:

  1. Clone the Repository:

    git clone https://github.com/Hunterdii/AI-Nexus.git
  2. Navigate to the Desired Project Directory:

    For example, for StyleScan:

    cd AI-Nexus/StyleScan

    For example, for GlycoTrack:

    cd AI-Nexus/GlycoTrack

    For example, for GradeCast:

    cd AI-Nexus/GradeCast

    For example, for ObjexVision:

    cd AI-Nexus/ObjexVision

    For example, for Iriswise:

    cd AI-Nexus/Iriswise

    For example, for DigitSense:

    cd AI-Nexus/DigitSense
  3. Install Dependencies: Install the required packages listed in the requirements.txt file:

    pip install -r requirements.txt
  4. Run the Application: Start the Streamlit app by running:

    streamlit run app.py
  5. Access the App in Browser: Open your browser and navigate to http://localhost:8501 to view and interact with the application.

📈 Future Enhancements

  • Adding more AI/ML models for healthcare and image recognition.
  • Deploying all apps for broader accessibility and public demos.
  • Introducing more advanced animations and dynamic visualizations.

💡 Customization & Contributions

Feel free to fork this repository, customize the UI, or add new machine learning models. Contributions are welcome! Make sure to submit a pull request with your proposed changes.


Happy exploring!