
How to program the kmeans algorithm in Python from scratch.
In this post I explain how the kmeans algorithm works in Python, its problems and how to solve them, programming the algorithm from scratch.
I consider the data as small pieces of a large puzzle. There are many, they are very different and you have to find a meaning for everything to fit together.
Therefore, I put all my effort and motivation to improve and learn every day to continue helping the clients I work with to go further thanks to the data
As a Data Scientist I try to follow CRISP-DM methodology and usually work with R or Python depending on the task to do.
Knowing more languages provides me of more tools to face problems and challenges.
To extract data from different data sources, to clean it and enriching it to improve the performance of Machine Learning models.
Train supervised models and undertake unsupervides models to add value and fulfill business objectives.
To communicate the insights obtained with CRISP-DM methodology to make results understandable and actionable to anyone needing them.
In this post I explain how the kmeans algorithm works in Python, its problems and how to solve them, programming the algorithm from scratch.
In this post I explain how you can create animations in Python to create much more impressive visualizations like barchart races.
In this post I explain everything about the kNN algorithm in R: distance measurements, when to use it, problems it has and much more.
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