DevelopersHubTask 🚀

This repository contains my assigned tasks and projects completed as part of the DevelopersHub program. The focus of this repository is on applying concepts of Artificial Intelligence, Machine Learning, and practical development skills.

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📌 Project Overview

This repository includes the following tasks:

🔹 Task 1: Data Analysis & Visualization

• Performed Exploratory Data Analysis (EDA)
• Used libraries like Pandas, Matplotlib, and Seaborn
• Generated insights from datasets (e.g., Iris dataset)

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🔹 Task 2: Machine Learning Model

• Built and trained ML models
• Implemented classification techniques
• Evaluated model performance using metrics

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🔹 Task 3: Heart Disease Prediction ❤️

• Dataset: UCI Heart Disease Dataset

• Steps:

  • Data Cleaning
  • Feature Selection
  • Model Training (Logistic Regression / Decision Tree)
  • Model Evaluation

• Goal: Predict risk of heart disease based on patient data

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🔹 Task 4: Health Chatbot 🤖

• Built using LLM (OpenAI API or open-source models)
• Handles general health-related queries
• Implemented using Python
• Demonstrates prompt engineering concepts

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🛠️ Technologies Used

• Python 🐍
• Google Colab
• Pandas
• NumPy
• Matplotlib / Seaborn
• Scikit-learn
• OpenAI API (for chatbot)

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📂 Repository Structure

DevelopersHubTask-/
│
├── DHubTask1.ipynb
├── DHubTask2.ipynb
├── DHubTask3.ipynb
├── DHubTask4.ipynb
├── README.md

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🚀 How to Run

1. Clone the repository:

git clone https://github.com/snippet-com/DevelopersHubTask-.git

2. Open notebooks in:

• Jupyter Notebook OR
• Google Colab

3. Install required libraries:

pip install pandas numpy matplotlib seaborn scikit-learn openai

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🎯 Learning Outcomes

• Hands-on experience with real datasets
• Understanding of ML workflows
• Practical implementation of AI concepts
• Experience with GitHub version control
• Basics of prompt engineering and chatbot development

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⭐ Note

This repository is part of my learning journey. Feedback and suggestions are always welcome!