0537 - 機器學習在物理
Machine Learning in Physics
教育目標 Course Target
In this course we will introduce the basic concepts of machine learning, including supervised and unsupervised learning, linear and logistic regression, regularization, neural networks, dimensional reduction, and etc. We will apply the method to physics related problems and learn how to make predictions and solve non-trivial problems.
In this course we will introduce the basic concepts of machine learning, including supervised and unsupervised learning, linear and logistic regression, regularization, neural networks, dimensional reduction, and etc. We will apply the method to physics related problems and learn how to make predictions and solve non-trivial problems.
參考書目 Reference Books
References:
Thoughtful machine learning
O'Relly, Matthew Kirk
http://mropengate.blogspot.com/2015/05/ai-supervised-learning.html
https://happycoder.org/2017/10/07/python-data-science-and-machine-learning-tutorial-introduction/
http://scikit-learn.org/stable/index.html
References:
Thoughtful machine learning
O'Relly, Matthew Kirk
http://mlopengate.blogspot.com/2015/05/ai-supervised-learning.html
https://happycoder.org/2017/10/07/python-data-science-and-machine-learning-tutorial-introduction/
http://scikit-learn.org/stable/index.html
評分方式 Grading
| 評分項目 Grading Method |
配分比例 Percentage |
說明 Description |
|---|---|---|
|
on line quizzes online quizzes |
20 | |
|
home works home works |
80 |
授課大綱 Course Plan
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相似課程 Related Courses
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課程資訊 Course Information
基本資料 Basic Information
- 課程代碼 Course Code: 0537
- 學分 Credit: 2-0
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上課時間 Course Time:Friday/1,2[ST019]
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授課教師 Teacher:吳桂光
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修課班級 Class:應物系2-4
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選課備註 Memo:電腦教室
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