课程信息

851,784 次近期查看

学生职业成果

35%

完成这些课程后已开始新的职业生涯

34%

通过此课程获得实实在在的工作福利
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
初级
完成时间大约为19 小时
英语(English)
字幕:英语(English)

您将获得的技能

Eigenvalues And EigenvectorsBasis (Linear Algebra)Transformation MatrixLinear Algebra

学生职业成果

35%

完成这些课程后已开始新的职业生涯

34%

通过此课程获得实实在在的工作福利
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
可灵活调整截止日期
根据您的日程表重置截止日期。
初级
完成时间大约为19 小时
英语(English)
字幕:英语(English)

提供方

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伦敦帝国学院

教学大纲 - 您将从这门课程中学到什么

内容评分Thumbs Up92%(30,972 个评分)Info
1

1

完成时间为 2 小时

Introduction to Linear Algebra and to Mathematics for Machine Learning

完成时间为 2 小时
5 个视频 (总计 28 分钟), 4 个阅读材料, 3 个测验
5 个视频
Motivations for linear algebra3分钟
Getting a handle on vectors9分钟
Operations with vectors11分钟
Summary1分钟
4 个阅读材料
About Imperial College & the team5分钟
How to be successful in this course5分钟
Grading policy5分钟
Additional readings & helpful references10分钟
3 个练习
Exploring parameter space20分钟
Solving some simultaneous equations15分钟
Doing some vector operations30分钟
2

2

完成时间为 2 小时

Vectors are objects that move around space

完成时间为 2 小时
8 个视频 (总计 44 分钟)
8 个视频
Modulus & inner product10分钟
Cosine & dot product5分钟
Projection6分钟
Changing basis11分钟
Basis, vector space, and linear independence4分钟
Applications of changing basis3分钟
Summary1分钟
4 个练习
Dot product of vectors15分钟
Changing basis15分钟
Linear dependency of a set of vectors15分钟
Vector operations assessment15分钟
3

3

完成时间为 3 小时

Matrices in Linear Algebra: Objects that operate on Vectors

完成时间为 3 小时
8 个视频 (总计 57 分钟)
8 个视频
How matrices transform space5分钟
Types of matrix transformation8分钟
Composition or combination of matrix transformations8分钟
Solving the apples and bananas problem: Gaussian elimination8分钟
Going from Gaussian elimination to finding the inverse matrix8分钟
Determinants and inverses10分钟
Summary59
2 个练习
Using matrices to make transformations30分钟
Solving linear equations using the inverse matrix30分钟
4

4

完成时间为 7 小时

Matrices make linear mappings

完成时间为 7 小时
6 个视频 (总计 53 分钟)
6 个视频
Matrices changing basis11分钟
Doing a transformation in a changed basis4分钟
Orthogonal matrices6分钟
The Gram–Schmidt process6分钟
Example: Reflecting in a plane14分钟
2 个练习
Non-square matrix multiplication20分钟
Example: Using non-square matrices to do a projection30分钟

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关于 数学在机器学习领域的应用 专项课程

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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