Machine learning Samenvattingen, Aantekeningen en Examens

Behaalde score: (17/20); Kwalitatieve, uitgebreide, duidelijke, allesomvattende (alle behandelde hoofdstukken) (128p) samenvatting (in Engels) van het vak Data Mining gebaseerd op het handboek, eigen notities en de slides. Recentelijk geschreven en gebruikt (2022).

Cheat Sheet for Machine Learning Exam: This cheat sheet includes all the necessary information to pass the Machine Learning exam. It contains relevant details from the lectures, and I could answer every question on the exam with it. Printing compatibility with campus printers has been tested and works good.

English Summary of Machine Learning course of Master Data Science and Society at Tilburg University. A summary of lecture materials, readings, and notes.

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...

A detailed summary of the lessons of Machine Learning taught by David Martens at the University of Antwerp. This is a summary of my own notes, the slides and the book Data Science for Business.

Summary of all the lectures of Machine Learning. It contains all the relevant material needed for the final exam.

Een complete samenvatting voor het vak "Toegepaste Machine Learning", waarin alle tentamenstof voor het eerste deeltentamen is verwerkt. Deze samenvatting biedt heldere uitleg van de belangrijkste concepten, praktische voorbeelden en overzichtelijke visualisaties om je voor te bereiden op het tentamen

Grade: 9.0. Extensive summary for the course Data Mining for Business and Governance. The summary contains the content of all lectures and tutorials (the theory, not the coding), including additional notes, examples and explanations. I also incorporated parts of the relevant chapters of the following books (in the form of supplementing the lecture content): (1) Data mining: concepts and techniques (3rd edition) by Jiawei Han, Micheline Kamber, Jian Pei (H-Book), (2) Data Mining: The Textbook by ...

Detailed summary of all lectures and additional notes, explanations and examples for the course "Machine Learning" at Tilburg University which is part of the Master Data Science and Society. Course was given by Ç. Güven during the second semester, block four of the academic year 2021 / 2022 (April to June 2022).

Summary of the APML course for information science on UU