/Pattern-Recognition-and-Machine-Learning

All labs and Projects done under the PRML course. [might have flaws]

Primary LanguageJupyter Notebook

PRML Course Assignments/Projects/Kaggle Competitions

This repository contains :

  1. Lab Assignments [Some datasets not available, however some labX.ipynbs contains link to dataset]
  2. Projects [Main Course Project, Bonus Project]
  3. Kaggle Competition [Kaggle 1 cant be revealed]

ML Models Covered in the Course

Supervised Learning

  • Decision Trees [Lab 2]
  • Boosting and Bagging on models [Lab 3]
  • Random Forests [Lab 3]
  • XGBoost [Lab 3, x]
  • LightGBM [Lab 3, x]
  • Naive Bayes [Lab 4, 5]
  • Linear Discriminant Analysis [Lab 5, 6]
  • Quadratic Discriminant Analysis [Lab 5]
  • Principal Component Analysis [Lab 6]
  • Multi-Layer Percepton [Lab 7]
  • Independant Component Analysis (ICA), FastICA [Lab 8]
  • Sequential Feature Selection [Lab 8]
  • Support Vector Machine [Lab 10]

Unsupervised Learning

  • K-Means Clustering [Lab 9]