Data-Viz on AW — notes & thoughts

Drawing a coffee plot, with LLMs ep0

Sat, 10 May 2025 21:28:43 -0500

LLM-assisted work?

Will the LLM take over us? Yes, no. Maybe.

The only thing I’m sure about is that those cool stuff are not able to assess the certainty of text (“opinions?”) they generate.

Moreover, In my humanly-limited experience, I have yet to see LLMs to meaningful contribute to any asset, i.e. to add valuable and extensive contribution to non-throaway code. All of this may seem strong, but hey, this does not mean productivity cannot be positively impacted.

Sparse notes

Wed, 01 Mar 2023 21:28:43 -0500

Data science

march Effect of irrelevant features - a nice experimental test
march Matrix factorizaton recap in 6minutes
march mean encodings: a comprehesive study, check also category_encoders sklearn library
march relationship between SVD and PCA + a comprehensive tutorial on arxiv
march Naive-Bayes classification from scratch
On Embeddings for Numerical Features in Tabular Deep Learning
Euclidean vs cosine distance

Data viz

Complimentary

Temporary

Staging area for links that will be forgotten soon:

march H&M personalized fashion reccomendation
march learning D3js + essential training + custom visuals into powerbi

What's all that for? Thinking of the BTC energy consumptions

Tue, 10 Jan 2023 21:28:43 -0500

I can remember the snow

Born on the cusp of the 90s, I was privileged to witness a period of great optimism and progress. The winds of freedom and democracy seemed to be blowing strong, and economies were thriving. One particularly noteworthy achievement from this time was the establishment of the Montreal Protocol, a treaty designed to phase out ozone-depleting substances, a move that has proven highly successful.

I have fond memories of being a child during this time, including TV commercials¹ that highlighted the importance of protecting polar bears. Even after all these years, the imagery of these ads stays with me, and their message continues to resonate, a testament to their powerful impact.

A (reasonably) complex radar chart

Fri, 11 Mar 2022 21:28:43 -0500

A radar (or spider) chart is a convenient method of displaying multivariate data in a form of 2-dimensional chart.

When I say convenient, I mean it is particularly well-accepted by people and gives a good intuition when comparing different items/subjects.

Think about comparing 2 (or more) football players in terms of dribbling, running speed, shots and pressure. Even with only four variables bar plot would become cumbersome to deal with and not immediate to perceive. That’s why they are particularly popular in sports analytics.