/CODFEST

Primary LanguageJupyter Notebook

CODSOFT Internship Repository

Welcome to my CODSOFT internship repository! This repository showcases the tasks I completed during my internship in the Machine Learning and Artificial Intelligence tracks.

GitHub issues GitHub forks GitHub stars GitHub license GitHub views

Table of Contents

Machine Learning Tasks

Task 1: Movie Genre Classification

In this task, I created a machine learning model to predict the genre of a movie based on its plot summary or other textual information. I utilized techniques like TF-IDF and classifiers such as Naive Bayes, Logistic Regression, and Support Vector Machines.

Task 1 Details and Code

Task 2: Credit Card Fraud Detection

For this task, I built a model to detect fraudulent credit card transactions using a dataset containing transaction information. I experimented with algorithms like Logistic Regression, Decision Trees, and Random Forests to classify transactions as fraudulent or legitimate.

Task 2 Details and Code

Task 3: Customer Churn Prediction

In Task 3, I developed a model to predict customer churn for a subscription-based service or business. I used historical customer data, including usage behaviour and demographics, and experimented with algorithms like Logistic Regression, Random Forests, and Gradient Boosting.

Task 3 Details and Code

Task 4: Spam SMS Detection

Task 4 involved building an AI model to classify SMS messages as spam or legitimate. I employed techniques like TF-IDF and classifiers like Naive Bayes, Logistic Regression, and Support Vector Machines to identify spam messages.

Task 4 Details and Code

Artificial Intelligence Tasks

Task 1: Chatbot with Rule-Based Responses

In this AI task, I created a simple chatbot that responds to user inputs based on predefined rules. I used if-else statements and pattern-matching techniques to identify user queries and provide appropriate responses.

Task 1 Details and Code

Task 2: Tic-Tac-Toe AI

Task 2 involved implementing an AI agent to play Tic-Tac-Toe against a human player. I used algorithms like Minimax with or without Alpha-Beta Pruning to make the AI player unbeatable.

Task 2 Details and Code

Task 3: Recommendation System

In Task 4, I created a simple recommendation system that suggests items to users based on their preferences. I employed techniques like collaborative filtering or content-based filtering to recommend movies, books, or products to users.

Task 3 Details and Code

Task 4: Face Detection and Recognition

For Task 5, I developed an AI application that can detect and recognize faces in images or videos. I used pre-trained face detection models and optionally added face recognition capabilities.

Task 4 Details and Code

Additional Information

  • You can find detailed code and explanations in the respective task folders for each task.
  • If you have any questions or need assistance, feel free to reach out to me via email at azlaanranjha2003@gmail.com.

I'm grateful for the opportunity provided by CODSOFT, and I hope you find my work on these tasks insightful and informative. Thank you for visiting my GitHub repository!

#codsoft #internship #machinelearning #artificialintelligence