In this post I explain how the kmeans algorithm works in Python, its problems and how to solve them, programming the algorithm from scratch.
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.