課程信息
196,872 次近期查看

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

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初級

完成時間大約為22 小時

建議:6 weeks of study, 2-5 hours/week...

英語(English)

字幕:英語(English), 希臘語, 西班牙語(Spanish)

您將獲得的技能

Linear RegressionVector CalculusMultivariable CalculusGradient Descent

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

初級

完成時間大約為22 小時

建議:6 weeks of study, 2-5 hours/week...

英語(English)

字幕:英語(English), 希臘語, 西班牙語(Spanish)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 4 小時

What is calculus?

10 個視頻 (總計 46 分鐘), 4 個閱讀材料, 6 個測驗
10 個視頻
Welcome to Module 1!1分鐘
Functions4分鐘
Rise Over Run4分鐘
Definition of a derivative10分鐘
Differentiation examples & special cases7分鐘
Product rule4分鐘
Chain rule5分鐘
Taming a beast5分鐘
See you next module!39
4 個閱讀材料
About Imperial College & the team5分鐘
How to be successful in this course5分鐘
Grading Policy5分鐘
Additional Readings & Helpful References5分鐘
6 個練習
Matching functions visually20分鐘
Matching the graph of a function to the graph of its derivative20分鐘
Let's differentiate some functions20分鐘
Practicing the product rule20分鐘
Practicing the chain rule20分鐘
Unleashing the toolbox20分鐘
2
完成時間為 3 小時

Multivariate calculus

9 個視頻 (總計 41 分鐘), 5 個測驗
9 個視頻
Variables, constants & context7分鐘
Differentiate with respect to anything4分鐘
The Jacobian5分鐘
Jacobian applied6分鐘
The Sandpit4分鐘
The Hessian5分鐘
Reality is hard4分鐘
See you next module!23
5 個練習
Practicing partial differentiation20分鐘
Calculating the Jacobian20分鐘
Bigger Jacobians!20分鐘
Calculating Hessians20分鐘
Assessment: Jacobians and Hessians20分鐘
3
完成時間為 3 小時

Multivariate chain rule and its applications

6 個視頻 (總計 19 分鐘), 4 個測驗
6 個視頻
Multivariate chain rule2分鐘
More multivariate chain rule5分鐘
Simple neural networks5分鐘
More simple neural networks4分鐘
See you next module!34
3 個練習
Multivariate chain rule exercise20分鐘
Simple Artificial Neural Networks20分鐘
Training Neural Networks25分鐘
4
完成時間為 2 小時

Taylor series and linearisation

9 個視頻 (總計 41 分鐘), 5 個測驗
9 個視頻
Building approximate functions3分鐘
Power series3分鐘
Power series derivation9分鐘
Power series details6分鐘
Examples5分鐘
Linearisation5分鐘
Multivariate Taylor6分鐘
See you next module!28
5 個練習
Matching functions and approximations20分鐘
Applying the Taylor series15分鐘
Taylor series - Special cases10分鐘
2D Taylor series15分鐘
Taylor Series Assessment20分鐘
4.7
325 個審閱Chevron Right

32%

完成這些課程後已開始新的職業生涯

24%

通過此課程獲得實實在在的工作福利

來自Mathematics for Machine Learning: Multivariate Calculus的熱門評論

創建者 JTNov 13th 2018

Excellent course. I completed this course with no prior knowledge of multivariate calculus and was successful nonetheless. It was challenging and extremely interesting, informative, and well designed.

創建者 SSAug 4th 2019

Very Well Explained. Good content and great explanation of content. Complex topics are also covered in very easy way. Very Helpful for learning much more complex topics for Machine Learning in future.

講師

Avatar

Samuel J. Cooper

Lecturer
Dyson School of Design Engineering
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David Dye

Professor of Metallurgy
Department of Materials
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A. Freddie Page

Strategic Teaching Fellow
Dyson School of Design Engineering

關於 伦敦帝国学院

Imperial College London is a world top ten university with an international reputation for excellence in science, engineering, medicine and business. located in the heart of London. Imperial is a multidisciplinary space for education, research, translation and commercialisation, harnessing science and innovation to tackle global challenges. Imperial students benefit from a world-leading, inclusive educational experience, rooted in the College’s world-leading research. Our online courses are designed to promote interactivity, learning and the development of core skills, through the use of cutting-edge digital technology....

關於 数学在机器学习领域的应用 專項課程

For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science. This specialization aims to bridge that gap, getting you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Data Science. In the first course on Linear Algebra we look at what linear algebra is and how it relates to data. Then we look through what vectors and matrices are and how to work with them. The second course, Multivariate Calculus, builds on this to look at how to optimize fitting functions to get good fits to data. It starts from introductory calculus and then uses the matrices and vectors from the first course to look at data fitting. The third course, Dimensionality Reduction with Principal Component Analysis, uses the mathematics from the first two courses to compress high-dimensional data. This course is of intermediate difficulty and will require Python and numpy knowledge. At the end of this specialization you will have gained the prerequisite mathematical knowledge to continue your journey and take more advanced courses in machine learning....
数学在机器学习领域的应用

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