PDEEC0049 Machine Learning 2017/18

18782: Machine Learning 2017/18
(offered under the Carnegie Mellon Portugal Program)

Messages:

Sample Exams

28/09/2017: recitation class on Oct 6th, 11am, room I304


09/08/2017: Students planning to take the course but not enrolled yet, please email me so I can add you to the mailing list. Thanks!


Grades
Grades

 

Assignments:


Assignment5

Assignment4

Assignment3

Assignment2

Assignment1

 


Project:

List of proposals

 


Additional Reading:

Machine-Learning Research - Four Current Directions

Top 10 algorithms in data mining

A Few Useful Things to Know about Machine Learning

Refresher on Probabilities and Information Theory: Chap 2, sections 2.1, 2.2, 2.3, 2.5, 2.6

Recitation Class: Linear-Algebra-Basics and multivariate probability/statistics and matlab script SVD and matlab script multivariate_normal


 

Lectures:

13/12/2017

Hidden Markov Models

Illustrative Matlab Code Illustrative Python Code

Class Exercises


05/12/2016

Unsupervised Learning

Class Exercises

 

28/11/2017

Unsupervised Learning

Class Exercises

 

21/11/2017

Introduction to Support Vector Machines + Short Intro to Support Vector Machines

Class Exercises

 

14/11/2017

Introduction to Neural Networks
python notebooks
Tensorflow links:
get_started
beginners
pros

Lecturers: Jose Costa Pereira

Class Exercises


06/11/2017

Model assessment, selection and Ensemble + Code

Class Exercises

 

24/10/2017

Classification: non-generative models

 

10/10/2017+17/10/2017

Bayesian Classifiers, Conditional Independence and Naive Bayes; Non Parametric Density Estimation

Class Exercises (heightWeightData)

 

03/10/2017

Regression Notes

Class Exercises

Data Bishop+regression python code

 

26/09/2017

Course Presentation

Pattern Recognition Concepts

Decision Trees

 

19/09/2017

Python and Machine Learning crash course: Intro and Conclusion and notebooks
Lecturers: Kelwin Fernandes and Ricardo Cruz

 

Tentative Calendar