Data Science

Such a renown Kaggle competition. Everyone into Machine Learning had tried to predict, who is more likely to survive: be it a family man, a gentlemen with expensive ticket, or a child? Or maybe someone holding a Royalty title? Yes, there is quite a number of features to learn for... [Read More]

Suppose you want to get top frequent words from a text. This task quickly reveals the caveats: there are swarms of words each with dozens of forms, all those n’t and ‘s and and also commas and periods… All these should be accounted for. Good for us, there are very... [Read More]

This is a solid and quick Machine Learning tutorial that leads through the steps of building a best prediction model. It allows to get understanding of the process and provides with code examples. I’ll be using Logistic Regressor and Trees (either Gradient Boosted or Ensembles are good), for saving space,... [Read More]

A handy cheatsheet on tools for model evaluation. Briefly explains key concepts, and ends up with Powerful GridSearch tool, providing code snippets. [Read More]

A useful cheatsheet of Machine Learning Algorithms, with brief description on best application along with code examples. The cheatsheet lists various models as well as few techniques (at the end) to compliment model performance. [Read More]

My NYC Schools Exploration project completed with interesting results and great visual. There is quite a number of code lines I’ve produced, all for the sake of finding out on how good can matplotlib be in drawing visuals. Turns out it is quite capable! Scroll to the very bottom to... [Read More]

It is always nice to have tidy and visually appealing graphs. As a matter of fact there is always a few lines of code necessary to beautify default graphs. This post contains those handy snippets and even more. There are few ways to follow: tune matplotlib-plotted graphs: dejunkify, set color... [Read More]