Machine learning is the study that allows computers to adaptively improve their performance with experience accumulated from the data observed. Our two sister courses teach the most fundamental algorithmic, theoretical and practical tools that any user of machine learning needs to know. This first course of the two would focus more on mathematical tools, and the other course would focus more on algorithmic tools. [機器學習旨在讓電腦能由資料中累積的經驗來自我進步。我們的兩項姊妹課程將介紹各領域中的機器學習使用者都應該知道的基礎演算法、理論及實務工具。本課程將較為著重數學類的工具，而另一課程將較為著重方法類的工具。]
機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations
機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations
Instructor: 林軒田
48,753 already enrolled
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Gain insight into a topic and learn the fundamentals.
4.9
(930 reviews)
Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
Learn at your own pace
96%
Most learners liked this course
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Assessments
2 assignments
Taught in Chinese (Traditional)
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There are 8 modules in this course
what machine learning is and its connection to applications and other fields
What's included
5 videos5 readings
your first learning algorithm (and the world's first!) that "draws the line" between yes and no by adaptively searching for a good line based on data
What's included
4 videos
learning comes with many possibilities in different applications, with our focus being binary classification or regression from a batch of supervised data with concrete features
What's included
4 videos
learning can be "probably approximately correct" when given enough statistical data and finite number of hypotheses
What's included
4 videos1 assignment
what we pay in choosing hypotheses during training: the growth function for representing effective number of choices
What's included
4 videos
test error can approximate training error if there is enough data and growth function does not grow too fast
What's included
4 videos
learning happens if there is finite model complexity (called VC dimension), enough data, and low training error
What's included
4 videos
learning can still happen within a noisy environment and different error measures
What's included
4 videos1 assignment
Instructor
Instructor ratings
4.9 (68 ratings)Offered by
Recommended if you're interested in Machine Learning
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4.9
930 reviews
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Showing 3 of 930
JG
4
Reviewed on Aug 17, 2017
許多名詞似乎是自創新詞，但都能很好地描述ML的理論課程的統計很吃重，難度的分配有些不均勻整體來說是非常適合有數學底子學生的扎實入門課程
JH
5
Reviewed on Sep 16, 2017
A great theoretical course in machine learning, and looking for he second part of the math foundation
ZL
4
Reviewed on Aug 26, 2020
林老师这部分课程内容偏理论，对数理基础有一定的要求。每次作业题需要认真思考，作业后面的编程部分也能锻炼实践能力，进一步巩固所学习的理论知识。总体来说质量不错，不过希望老师以后能以后对课件里面的问题进行总结的时候可以不用太story-like，或者说更简练一点，我认为这样可以有助于学习暂停视频并好好理解。
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