AI_Intern_at_IBM

Artificial Intelligence & Machine Learning Based Programs - Internship Daily Tasks

Welcome to the AI-ML Internship Daily Tasks Repository. This repository serves as a comprehensive record of my accomplishments throughout the AI-ML internship with IBM. It gathered all tasks, their corresponding code, and detailed explanations in a well-structured manner.

Table of Contents

• Internship Details
• Repository Structure
• Technologies Used
• Getting Started
  • Prerequisites
  • Installation
  • Running the Backend
  • Running the Frontend
• Project Structure
• Contributing
• License
• Contact

Internship Details

• Internship Program - Artificial Intelligence & Machine Learning
• Company/Organization - IBM
• Internship Period - 5 Months

Repository Structure

This repository is organized by daily task. Each task has its own dedicated directory containing the source code and an optional README.md file for further explanations.

Technologies Used

• Backend: Python, TensorFlow, PyTorch
• Frontend: Streamlit, Flask with Jinja2, TensorFlow.js, Dash by Plotly
• Database: MySQL, redis
• Code Editor: Jupyter Notebook, Google Colab, VS Code etc
• Self-paced Content

Getting Started

Prerequisites

• Python 3.11.4 or higher
• streamlit and pip
• MySQL

Installation

1. Clone the repository:

   ```bash git clone https://github.com/yourusername/ai-ml-internship.git cd ai-ml-internship

2. Install dependencies and start the application:

   ```bash pip install streamlit run app.py

Contribution Guidelines

Thank you for considering contributing to this project! Here are a few guidelines to get started:

How to Contribute

1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Make your changes.
4. Test your changes thoroughly.
5. Submit a pull request.

Reporting Issues

If you find a bug or have a feature request, please create an issue on GitHub.

Thank you for your contributions!

Contact

If you have any questions or suggestions, feel free to reach out to me at mohitsscs1980@gmail.com

Let’s Start Coding!

As my progress through the internship program, diligently add my completed tasks to this repository for easy reference and showcasing my progress.

Happy Coding!