News
Tutorial Preferences in CMSWritten on 15.10.24 by Kavya Gupta Dear students, Please select your preferences by Friday 12 PM. We will be starting the tutorials from next week. See you all on Thursday at 4pm at the… Read more Dear students, Please select your preferences by Friday 12 PM. We will be starting the tutorials from next week. See you all on Thursday at 4pm at the GHH! Prof. Isabel Valera and Dr. Kavya Gupta
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Select your preferences on the tutorial slots before Friday October 18th at 12pmWritten on 15.10.24 by Isabel Valera Dear students, We have now enabled the option for you to select your preferences regarding the tutorial slots. Please add your preferences before this Friday, 18th of October, at 12pm. We will inform you on the tutorial assignment shortly afterwards, i.e., on Friday afternoon.
See you all… Read more Dear students, We have now enabled the option for you to select your preferences regarding the tutorial slots. Please add your preferences before this Friday, 18th of October, at 12pm. We will inform you on the tutorial assignment shortly afterwards, i.e., on Friday afternoon.
See you all on Thursday at 4pm at the GHH! Prof. Isabel Valera and Dr. Kavya Gupta
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Elements of Machine Learning
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Summary
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In this course we will discuss the foundations – the elements – of machine learning. In particular, we will focus on the ability of, given a data set, to choose an appropriate method for analyzing it, to select the appropriate parameters for the model generated by that method, and to assess the quality of the resulting model. Both theoretical and practical aspects will be covered. Lectures will start on October 17th! |
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Prerequisites
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The course is targeted at students in computer science, data science and AI, cybersecurity, bioinformatics, math, and general sciences with a mathematical background. Students should know the basics of programming, proof techniques, linear algebra, and statistics, for example by having taken Programming I and II (for programming), Mathematics for Computer Scientists I and II (for linear algebra), and then either Statistics Lab or Mathematics for Computer Scientists III (for statistics). |
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Type |
Basic Lecture (6 ECTS) for BSc DSAI, CySec, and Computer Science; Advanced Lecture (6 ECTS) for all others except for the M.Sc. Cybersecurity. |
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| Lectures |
Thursdays, 16–18 o'clock in person in E.2.2 Lecture Hall 0.01 (Günter Hotz Hörsaal) - Lectures will be recorded (more details coming soon). |
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| Assignments |
5 assignment sheets, including theoretical and programming exercises. |
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Tutorials
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All tutorials will be in person and take place at HS003 in E1.3. Monday : 10-12 |
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| Exams | Main Exam - 14-17h, 19th February, 2025 Re-exam - 14-17h, 20th March, 2025 |
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Office Hours
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Prof. Dr. Isabel Valera and Dr. Kavya Gupta: after each lecture |
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Language |
English |
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| Schedule |
Tentative Schedule of the Lectures.
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