Math for AI - Machine Learning Algorithms

Group 6 - Math for AI, AI23 @ HCMUS

This repository contains implementations of various machine learning / deep learning algorithms, including Linear Regression, PCA&Clustering, Naive Bayes Classifier, CLIP. The code is designed for educational purposes, providing a clear and concise understanding of the mathematical foundations and practical applications of these algorithms.

Contents

• Linear Regression: Implementation of linear regression for predictive modeling.
• PCA&Clustering: Implementation of PCA, KMeans and Gaussian Mixture Model (GMM) for classification tasks on Iris and ABIDE II datasets.
• Naive Bayes Classifier: Implementation of Bag-of-Words technique, Naive Bayes Classifier model for classification task on Enron-Spam dataset.
• CLIP: Explanation about CLIP - a foundation model in Vision-Language Models.

Requirements

To run the code in this repository, you need the following Python libraries:

• numpy
• matplotlib
• pandas
• scikit-learn (PCA&Clustering)
• transformer (CLIP)

Install the required libraries using:

pip install numpy matplotlib pandas scikit-learn