Tilburg University (UVT) • Data Science & Society

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.

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

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Discover a comprehensive and valuable overview of lectures, coupled with additional notes, detailed explanations, and illustrative examples for the "Machine Learning" course within the Master's in Data Science and Society program. Elevate your understanding with this resourceful compilation.

Provides all basic concepts you need to know of Machine learning with easy to read and understandable language in question answer format. **Best for revision of basic concepts in machine learning.

Summary of the most important themes of the lectures of Data Mining for Government and Business. This summary clearly describes all the concepts explained in the lectures. Clearly marking where a new week starts and an old week ends. Bullet point separated summary.

Course grade: 9.0. Extensive summary for the course Analysis of Customer Data. The summary contains the content of all lectures and tutorials, including additional notes and explanations. The course is taught by dr. B. Cule and dr. G. Napoles, as part of the MSc Data Science & Society at Tilburg University.

Course grade: 8.0. Extensive summary for the course Bayesian Multilevel Models. The summary contains the content of all lectures and tutorials, including additional notes and explanations. The course is taught by dr. B. Nicenboim, as part of the MSc Data Science & Society at Tilburg University. Note that the content (including the coding) of the tutorials is included, but not the answers to the exercises.

Summary of notebooks Data Processing advanced

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 ...