This repository contains a collection of assignments for the Statistical Methods in AI Spring 2023 course prepared during my tenure as a Teaching Assistant along with other TAs. Each assignment is organized into its own directory and includes a set of questions, code, and data related to various topics in AI and machine learning.
- K Nearest Neighbour
rollnumber_A1_Q1.ipynb
- Decision Trees
rollnumber_A1_Q2.ipynb
- Linear Regression
rollnumber_A1_Q3.ipynb
- Clustering
Q1.ipynb
- Principal Component Analysis
Q2.ipynb
- Multinomial Naive Bayes
Q3.ipynb
- Gaussian Naive Bayes
Q4.ipynb
- CNNs
Let's Dive into CNNs.ipynb
- Gaussian Mixture Models
GMM.ipynb
- Multi-Layer Perceptron
Knowing MLPs.ipynb
- Support Vector Machine
SVM.ipynb
To make the best use of this repository, you can clone it to your local machine and access the assignments you need. Each assignment directory contains the necessary files to work on the questions and complete the tasks.
If you find any issues or have suggestions for improvements, please feel free to create a pull request or open an issue. We welcome contributions and feedback from fellow learners and contributors.
Happy learning!