Machine Learning

Machine Learning summary for the 2nd year of artificial intelligence study. All chapters and lectures before the exam.

This summary contains all material discussed in the lectures (1-13) of Machine Learning taught at the Vrije Universiteit Amsterdam to third year Business Analytics, Information Science, Computer Science and Artificial Intelligence bachelor students. It is quite extensive, contains a lot more than just theoretical formulas (I think it is hard to memorise them without knowing some background) so everything I wrote is explained with a sketch, example or some extra information that all helped me t...

This summary is comprehensive, but contains everything you need to get a good exam grade! I myself got an 8.5, so this should work out! In addition to the summary, I would also take the practice exam (for the application questions), then you are ready to go!

This document provides a relatively extensive summary of the machine learning course, given in the second year of the AI bachelor. It covers all video's used as lecture material in the year 2020 - 2021, during the COVID breakout.

Lectures 1 to 13 summarised > everything you need to know for the exam!

College aantekeningen Machine Learning Week 1 - 5 (2 colleges per week)

A handwritten overview of the course Machine Learning. It includes all the important aspects of the course and has helped me to pass it.

This is a solution manual for pattern recognition and machine learning. It contains detailed solutions for the questions in the relevant book. Helpful for understanding and verifying the approach and correctness of solutions.

This is a summary of all lectures in the subject of machine learning. Topics that are coverd: - offline/online learning - Methodology - Probability - Neural network - Backpropagation - Deep learning - Decision tree - Netflix