关于此 专项课程

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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.
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初级
完成课程大约需要 4 个月
建议进度:4 小时/周
英语(English)
可分享的证书
完成后获得证书
100% 在线课程
立即开始,按照自己的计划学习。
灵活的计划
设置并保持灵活的截止日期。
初级
完成课程大约需要 4 个月
建议进度:4 小时/周
英语(English)

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此专项课程包含 3 门课程

课程1

课程 1

Mathematics for Machine Learning: Linear Algebra

4.7
10,132 个评分
2,041 条评论
课程2

课程 2

Mathematics for Machine Learning: Multivariate Calculus

4.7
4,866 个评分
870 条评论
课程3

课程 3

Mathematics for Machine Learning: PCA

4.0
2,681 个评分
673 条评论

提供方

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伦敦帝国学院

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