This repository contains four different AI projects aimed at solving various tasks using machine learning and computer vision techniques. Each project addresses a specific problem and utilizes different algorithms and models for its solution.
Description:
This sentiment analysis model utilizes logistic regression to determine the sentiment conveyed in a given tweet or text. It's trained to classify the sentiment as positive or negative based on the content of the statement.
Technologies Used:
- Logistic Regression
- Natural Language Processing (NLP)
Link: Tweets Sentiment Analysis Algorithm Repo
Description:
The face recognition project aims to perform face recognition using OpenCV, Haar cascade classifier for face detection, and LBPHFace recognizer. It captures faces, assigns IDs, detects faces using Haar cascade classifier, and recognizes faces in real-time.
Technologies Used:
- OpenCV
- Haar Cascade Classifier
- LBPHFace Recognizer
Link: Face Recognition Project Repo
Description:
This model employs the K Nearest Neighbours (KNN) algorithm to offer personalized movie suggestions by analyzing the preferences of similar users. It predicts how a target user would rate unseen films based on shared behaviors, providing accurate and relevant recommendations.
Technologies Used:
- K Nearest Neighbours (KNN)
- Collaborative Filtering
- MovieLens Dataset
Link: Personalized Movie Recommendations Repo
Description:
The Trash Detection project is aimed at detecting and classifying different types of trash in images using artificial intelligence techniques. It utilizes machine learning models to automatically identify and categorize various types of waste commonly found in images.
Technologies Used:
- YOLO v8 Model
- TACO Dataset
Link: Trash Detection AI Repo
Contributions to these projects are welcome! If you find any issues or have suggestions for improvements, feel free to open an issue or submit a pull request in the respective project repositories.