CODSOFT-ARTIFICIAL-INTELLIGENCE-INTERNSHIP

Aries A.I Chatbot

Task 1: Chatbot Implementation

Description: This project involves creating a voice-activated chatbot named Aries, capable of recognizing greetings, answering queries about itself, telling jokes, providing interesting facts, and handling various user inputs. The chatbot also features music playback functionality and can open web pages like YouTube, GitHub, and LinkedIn. It aims to deliver an interactive and engaging user experience while enhancing fundamental AI programming skills.

Usage:

1. Run the Python script.
2. The chatbot greets and prompts for input.
3. Speak your query or command.
4. Type 'exit' or say 'goodbye' to end the conversation.

Author:

Jaivansh Chawla

Acknowledgments:

Thanks to Codsoft Team for the valuable opportunity during the Codsoft AI Internship.

Tic-Tac-Toe with Mini-Max Algorithm

Task: Game Implementation

Description: This project implements a Tic-Tac-Toe game where the player competes against a computer opponent. The computer uses the Mini-Max algorithm to make optimal moves, ensuring challenging gameplay. The player can choose to play first or second, and the game will display the current board state after each move.

Usage:

1. Run the Python script.
2. Choose whether you want to play first or second.
3. Enter your move by specifying a position from 1 to 9.
4. The computer will make its move automatically.
5. The game will continue until there is a winner or a draw.

Author:

Jaivansh Chawla

Acknowledgments:

Thanks to everyone who contributed to the development of this project.

Facial Recognition Application

Description

This project implements a real-time facial recognition application using OpenCV. The application captures video from the webcam and detects faces in the live feed using a pre-trained Haar Cascade classifier.

Features

• Real-time face detection from webcam feed
• Draws rectangles around detected faces
• Full-screen display of the live video feed

Usage

1. Ensure you have the required libraries installed (opencv-python).
2. Update the path to the Haar Cascade classifier in the code.
3. Run the script to start the facial recognition application.
4. Press 'a' to exit the application.

Requirements

• Python 3.x
• OpenCV library

Author:

Jaivansh Chawla

Acknowledgments

Thanks to the OpenCV community for their resources and documentation that made this project possible.