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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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完成後獲得證書
100% 在線課程
立即開始,按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
初級
完成課程大約需要 4 個月
建議進度:4 小時/週
英語(English)
可分享的證書
完成後獲得證書
100% 在線課程
立即開始,按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
初級
完成課程大約需要 4 個月
建議進度:4 小時/週
英語(English)

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此專項課程包含 3 門課程

課程1

課程 1

Mathematics for Machine Learning: Linear Algebra

4.7
10,139 個評分
2,041 條評論
課程2

課程 2

Mathematics for Machine Learning: Multivariate Calculus

4.7
4,874 個評分
870 條評論
課程3

課程 3

Mathematics for Machine Learning: PCA

4.0
2,687 個評分
673 條評論

提供方

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伦敦帝国学院

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