math-for-ml

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Blank notebooks and solutions for the Mathematics for Machine Learning specialization by Imperial College of London on Coursera.

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최종 버전 다운로드 (.zip)

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# Mathematics for Machine Learning

Blank notebooks and [solutions](https://github.com/claramatos/math-for-ml/tree/solutions) for the Mathematics for Machine Learning 
specialization by Imperial College of London on [Coursera](https://www.coursera.org/specializations/mathematics-machine-learning).

## Linear Algebra

[Identifying special matrices](https://github.com/claramatos/math-for-ml/blob/master/linear-algebra/IdentifyingSpecialMatrices.ipynb)

[Gram-Schmidt process](https://github.com/claramatos/math-for-ml/blob/master/linear-algebra/GramSchmidtProcess.ipynb)

[Reflecting Bear](https://github.com/claramatos/math-for-ml/blob/master/linear-algebra/ReflectingBear.ipynb)

[PageRank](https://github.com/claramatos/math-for-ml/blob/master/linear-algebra/PageRank.ipynb)

## Multivariate Calculus

[The Sandpit](https://github.com/claramatos/math-for-ml/blob/master/multivariate-calculus/TheSandpit.ipynb)

[The Sandpit - Part 2](https://github.com/claramatos/math-for-ml/blob/master/multivariate-calculus/TheSandpitPart2.ipynb)

[Backpropagation](https://github.com/claramatos/math-for-ml/blob/master/multivariate-calculus/Backpropagation.ipynb)

Gradient descent in a sandpit

[Fitting the distribution of heights data](https://github.com/claramatos/math-for-ml/blob/master/multivariate-calculus/FittingTheDistributionOfHeightsData.ipynb)

## PCA

[Mean/covariance of a dataset + effect of a linear transformation](https://github.com/claramatos/math-for-ml/blob/master/pca/week1.ipynb)

[Programming Assignment: Inner products and angles](https://github.com/claramatos/math-for-ml/blob/master/pca/week2.ipynb)

[Orthogonal projections](https://github.com/claramatos/math-for-ml/blob/master/pca/week3.ipynb)

[Principal Components Analysis (PCA)](https://github.com/claramatos/math-for-ml/blob/master/pca/week4.ipynb)

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