Applied Machine Learning
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Teaching Plan:
See attached Syllabus.
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Leader of Teaching Group:
Zhongyi Hu
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Course Introduction:
This class cover a hands-on approach to data analytics and machine learning. We will study commonly used machine learning techniques, including linear regression, logistic regression, KNN, neural networks, support vector machines, decision trees and ensemble learning. We will also discuss methods to address pracitical issues such as data preparation, model selection and evaluation. Apart from applying models, we will also discuss latest academic research and industry applications with MLs.
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Venue:
Building 1, Campus of Humanities and Sciences, WHU
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Schedule:
Thursday, 18:45-20:50
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Testing Method:
The final grade will be based on the following components:
• Weekly assignment - 20%
• Mini-project 1 - 20%
• Mini-project 2 - 20%
• Final report - 40%
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Target Students:
Master students
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Discipline:
Management Science and Engineering
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Teacher:
Zhongyi Hu
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Class classroom:
209
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School Year:
2018-2019
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Semester:
Autumn Term
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Course number:
201800151
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Credits:
2.0
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Course Type:
Postgraduate Course
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Top-Quality Courses or Not:
yes
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Required Class Hours:
32.0
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Courses and reference books:
www.datacamp.com
