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Lydia Nemec
Lydia Nemec

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Published in Towards Data Science

·Jan 16

Principal Component Analysis (PCA): A Physically Intuitive Mathematical Introduction

The principal component analysis (PCA) involves rotating a cloud of data points in Euclidean space such that the variance is maximal along the first axis, the so-called first principal component. The principal axis theorem ensures that the data can be rotated in such away. …

Machine Learning

9 min read

Principal Component Analysis (PCA)
Principal Component Analysis (PCA)

Aug 15, 2019

Documenting Your Data-Science Project — A Guide To Publish Your Sphinx Code Documentation

In this article, we like to give you a step by step guide on how to document your Python Data Science project effectively as part of your machine learning model development. You find our example code on GitHub. The solution, we propose, ensures that your documentation is version controlled, shipped…

Data Science

7 min read

Documenting Your Data-Science Project — A Guide To Publish Your Sphinx Code Documentation
Documenting Your Data-Science Project — A Guide To Publish Your Sphinx Code Documentation
Lydia Nemec

Lydia Nemec

I am a Lead Data Scientist with a background in computational physics, numerics and machine learning bridging the way from research to innovative solutions.

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