Pen & Paper Exercises in Machine Learning

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Conflicts of Interest

Identified Weaknesses

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Paper Summary

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Pen & Paper: Sharpen Your Machine Learning Skills (But Don't Forget Your Laptop Eventually)

This collection presents various pen-and-paper exercises targeting core machine learning concepts, particularly unsupervised learning, inference, and model training. While the detailed solutions help develop mathematical understanding, the absence of associated computer exercises hinders practical skill-building. The book covers linear algebra, optimization, graphical models, expressive power of graphical models, factor graphs, message passing, inference for Hidden Markov Models, model-based learning, and sampling and Monte Carlo integration.

Possible Conflicts of Interest

The author acknowledges previous affiliations with the University of Helsinki and the University of Edinburgh. No other conflicts of interest identified.

Identified Weaknesses

Limited scope of Machine Learning topics

The exercises provided do not cover all areas of Machine Learning, with a primary focus on unsupervised methods, inference and learning.

Lack of practical computer exercises

Despite encouragement for supplemental computer exercises, the exclusive focus on pen-and-paper exercises may not be sufficient for practical application in a field heavily reliant on computational tools.

Missing suggested computer exercises

The preface states that computer exercises would deepen understanding; however, there's no provision of such exercises, creating a gap between theoretical learning and practical application.

Rating Explanation

Well-structured collection of exercises beneficial for theoretical understanding, though the lack of accompanying computer exercises slightly limits practical application. Detailed solutions and a focus on mathematical foundations enhance its educational value.

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