COMP90049-Intro-of-Machine-Learning

This is the showcase repository to present the project and teaching materials of COMP90049 of The University of Melbourne in 2021 Semester 1.

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
Assignment 1		Assignment 1
Assignment 2		Assignment 2
Assignment 3		Assignment 3
Python Coding Resources		Python Coding Resources
Week 1 Introduction		Week 1 Introduction
Week 10 - Semisupervised & Anomaly Detection		Week 10 - Semisupervised & Anomaly Detection
Week 11 - Fairness in ML (ethics & Bias)		Week 11 - Fairness in ML (ethics & Bias)
Week 12 - Fairness in ML (Discusssin & Case Study) & Final Review		Week 12 - Fairness in ML (Discusssin & Case Study) & Final Review
Week 2 K-Nearest Neighbour & Probability		Week 2 K-Nearest Neighbour & Probability
Week 3 Optimization & Naive Bayes		Week 3 Optimization & Naive Bayes
Week 4 - Model Evaluation & Feature Selection		Week 4 - Model Evaluation & Feature Selection
Week 5 - Iterative Optimization & Logistic Regression		Week 5 - Iterative Optimization & Logistic Regression
Week 6 - Perceptron & Neutral Network		Week 6 - Perceptron & Neutral Network
Week 7 - Backpropagation & Evaluation Revisited		Week 7 - Backpropagation & Evaluation Revisited
Week 8 - Academic Writing & Decision Tree		Week 8 - Academic Writing & Decision Tree
Week 9 - Ensembles & Unsupervised Learning		Week 9 - Ensembles & Unsupervised Learning
Workshop		Workshop
README.md		README.md

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