Update week39.do.txt
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TITLE: Week 39: Optimization and Gradient Methods
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AUTHOR: Morten Hjorth-Jensen {copyright, 1999-present|CC BY-NC} at Department of Physics, University of Oslo & Department of Physics and Astronomy and Facility for Rare Isotope Beams, Michigan State University
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AUTHOR: Morten Hjorth-Jensen {copyright, 1999-present|CC BY-NC} at Department of Physics, University of Oslo
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DATE: Week 39
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!split
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===== Plan for week 39, September 23-27, 2024 =====
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===== Plan for week 39, September 22-26, 2025 =====
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!split
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===== Lecture Monday September 23 =====
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===== Lecture Monday September 22 =====
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!bblock Material for the lecture on Monday September 23
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!bblock Material for the lecture on Monday September 22
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* Repetition of Logistic regression equations and classification problems and discussion of Gradient methods. Examples on how to implement Logistic Regression and discussion of gradient methods
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* Stochastic Gradient descent with examples and automatic differentiation (theme also for next week).
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* "Video of lecture":"https://youtu.be/ISGpTC28Vmk"
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* "Whiteboard notes":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember23.pdf"
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# * "Video of lecture":"https://youtu.be/ISGpTC28Vmk"
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# * "Whiteboard notes":"https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesSeptember23.pdf"
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* Readings and Videos:
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* These lecture notes
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* For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.
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!split
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===== Lecture Monday September 23, Optimization, the central part of any Machine Learning algortithm =====
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===== Lecture Monday September 22, Optimization, the central part of any Machine Learning algortithm =====
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The first few slides here are a repetition from last week.
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