EE413-PRML-Lab

This repository contains files related to Pattern Recognition and Machine Learning Lab (Autumn 2022).

Assignments Included

Lab 1 - Probability Theory

1. Sampling from Uniform Distribution
2. Sampling from Gaussian Distribution
3. Categorical Sampling
4. Central Limit Theorem
5. Computing π using Sampling
6. Monty Hall Problem

Lab 2 - Linear Algebra

1. System of Equations: Full Rank, Square Matrix
2. System of Equations: Full Rank, Non-Square Matrix
3. System of Equations: Non-Full Rank Matrix

Lab 3 - Convex Optimization

1. Minimizing $f(x) = x^{2} + x + 2$
2. Minimizing $f(x) = xsinx$
3. Minimizing $f(x, y) = x^{2} + y^{2} + 2x + 2y$
4. Minimizing $f(x, y) = xsinx + ysiny$

Lab 4 - Clustering - I

1. Partition Based Clustering (K-Means)
2. Model Based Clustering (GMM)
3. Applications of Clustering: Iris Flower Dataset

Lab 5 - Regression - I

1. Fitting of a Line
2. Fitting of a Plane
3. Fitting of an M-Dimensional Hyperplane
4. Applications of Regression: Salary Prediction

Lab 6 - Regression - II

1. Polynomial Regression
2. The Shortcomings of Linear Regression
3. Logistic Regression
4. Classification of Circular-Separated data using LogReg
5. MultiClass Logistic Regression

Lab 7 - Clustering - II

1. Density Based Clustering (DBSCAN)
2. Partition Based Clustering (Fuzzy C-Means)
3. Hierarchial Clustering (Agglomerative Approach)
4. Applications of Clustering: MNIST Digit Dataset

Lab 8 - Classification

1. Support Vector Machines
2. K-Nearest Neighbours
3. Applications of Classification: MNIST Digit Dataset

Lab 9 - Naïve Bayes

1. Binary Classification
2. Sentiment Analysis

Lab 10 - Hidden Markov Model

1. Evaluation Problem (Forward, Backward Algorithms)
2. Learning Problem (Baum Welch Algorithm)
3. Decoding Problem (Viterbi Algorithm)
4. Using decoder from hmmlearn package

Lab 11 - Dimensionality Reduction

1. PCA (Principal Component Analysis)
2. LDA (Linear Discriminant Analysis)

Let your plans be dark and impenetrable as night, and when you move, fall like a thunderbolt. — Sun Tzu, The Art of War