Update README.md

README.md

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-# Gemini Data Science Chatbot
-
-A Data Science chatbot powered by the Google Gemini model that answers questions related to machine learning, statistics, Python, and data analysis.
-
-This project demonstrates how to integrate a Large Language Model with a web interface to build an interactive AI assistant for learning and solving data science problems.
-
----
-
-## Features
-
-- Answer machine learning and data science questions
-- Generate Python code examples
-- Explain statistics and ML concepts
-- Interactive web chatbot interface
-- Command line chatbot version
-- Model availability checker
-
----
-
-## Tech Stack
-
-- Python
-- Google Gemini API
-- Gradio (for web interface)
-- python-dotenv
-
----
-
-## Project Structure
-
-```
-gemini-data-science-chatbot/
-│
-├── app.py
-├── simple_chat.py
-├── gemini_model_check.py
-├── requirements.txt
-├── .env
-└── README.md
-```
-
-**app.py**  
-Gradio-based web chatbot interface.
-
-**simple_chat.py**  
-Command line chatbot version.
-
-**gemini_model_check.py**  
-Script used to check which Gemini models are available for the API key.
-
-**requirements.txt**  
-Project dependencies.
-
----
-
-## Installation
-
-Clone the repository
-
-```bash
-git clone https://github.com/YOUR_USERNAME/gemini-data-science-chatbot.git
-cd gemini-data-science-chatbot
-```
-
-Install dependencies
-
-```bash
-pip install -r requirements.txt
-```
-
-Create a `.env` file inside the project folder
-
-```
-GEMINI_API_KEY=your_api_key_here
-```
-
----
-
-## Run the Web Chatbot
-
-Run the Gradio application
-
-```bash
-python app.py
-```
-
-Then open your browser and go to
-
-```
-http://127.0.0.1:7860
-```
-
----
-
-## Run the Command Line Chatbot
-
-```bash
-python simple_chat.py
-```
-
----
-
-## Check Available Gemini Models
-
-```bash
-python gemini_model_check.py
-```
-
-This script lists the models available for your API key.
-
----
-
-## Example Questions
-
-You can ask questions such as:
-
-- What is overfitting in machine learning?
-- Explain gradient descent
-- Write Python code for logistic regression
-- Difference between bagging and boosting
-- Explain bias vs variance
-
----
-
-## Future Improvements
-
-- Add conversation memory
-- Add dataset upload and analysis
-- Implement Retrieval Augmented Generation (RAG)
-- Deploy the chatbot online
-- Add streaming responses
-
----
-
-## Author
-
-Madan Dahiphale
-
-LinkedIn  
+---
+title: Gemini Data Science Chatbot
+emoji: 🤖
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+app_file: app.py
+pinned: false
+---
+
+# Gemini Data Science Chatbot
+
+A Data Science chatbot powered by the Google Gemini model that answers questions related to machine learning, statistics, Python, and data analysis.
+
+This project demonstrates how to integrate a Large Language Model with a web interface to build an interactive AI assistant for learning and solving data science problems.
+
+---
+
+## Features
+
+- Answer machine learning and data science questions
+- Generate Python code examples
+- Explain statistics and ML concepts
+- Interactive web chatbot interface
+- Command line chatbot version
+- Model availability checker
+
+---
+
+## Tech Stack
+
+- Python
+- Google Gemini API
+- Gradio (for web interface)
+- python-dotenv
+
+---
+
+## Project Structure
+
+```
+gemini-data-science-chatbot/
+│
+├── app.py
+├── simple_chat.py
+├── gemini_model_check.py
+├── requirements.txt
+├── .env
+└── README.md
+```
+
+**app.py**  
+Gradio-based web chatbot interface.
+
+**simple_chat.py**  
+Command line chatbot version.
+
+**gemini_model_check.py**  
+Script used to check which Gemini models are available for the API key.
+
+**requirements.txt**  
+Project dependencies.
+
+---
+
+## Installation
+
+Clone the repository
+
+```bash
+git clone https://github.com/YOUR_USERNAME/gemini-data-science-chatbot.git
+cd gemini-data-science-chatbot
+```
+
+Install dependencies
+
+```bash
+pip install -r requirements.txt
+```
+
+Create a `.env` file inside the project folder
+
+```
+GEMINI_API_KEY=your_api_key_here
+```
+
+---
+
+## Run the Web Chatbot
+
+Run the Gradio application
+
+```bash
+python app.py
+```
+
+Then open your browser and go to
+
+```
+http://127.0.0.1:7860
+```
+
+---
+
+## Run the Command Line Chatbot
+
+```bash
+python simple_chat.py
+```
+
+---
+
+## Check Available Gemini Models
+
+```bash
+python gemini_model_check.py
+```
+
+This script lists the models available for your API key.
+
+---
+
+## Example Questions
+
+You can ask questions such as:
+
+- What is overfitting in machine learning?
+- Explain gradient descent
+- Write Python code for logistic regression
+- Difference between bagging and boosting
+- Explain bias vs variance
+
+---
+
+## Future Improvements
+
+- Add conversation memory
+- Add dataset upload and analysis
+- Implement Retrieval Augmented Generation (RAG)
+- Deploy the chatbot online
+- Add streaming responses
+
+---
+
+## Author
+
+Madan Dahiphale
+
+LinkedIn  
 https://www.linkedin.com/in/madandahiphale