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.
- 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.
To run the code in this repository, you need the following Python libraries:
numpymatplotlibpandasscikit-learn(PCA&Clustering)transformer(CLIP)
Install the required libraries using:
pip install numpy matplotlib pandas scikit-learn