avid learner who loves a challenge

from "Limitless", by Jim Kwik

Portfolio

technical projects

You can find some of my projects here: Projects - coding .

The projects cover several basic skills in Data Science/Machine Learning:

  • Data wrangling/cleaning/engineering. It is important to fully undertand all aspects of the data from its collection source to its utilization. The approach to pre-process depends completely on how well you understand it.

    One secret I want to share: data wrangling is 10% skill, 90% anger management. Here is an example shared by Peter Norvic from Google

  • Statistics: in general you don't need fancy statistics unless you are answering the wrong question. Spend time asking the correct question/s.
  • Machine Learning: 1) feature seletion is one of the most relevant aspects in any analysis. Regarding model selection, it is important not which one had the highest score but to answer what worked and why. The reason is that the data in your hands is ALWAYS a subset of the REAL DATA you will encounter.
  • Visualization: It is a powerful tool to convey information. Learning some basic tools like Matplotlib, Plotly or Tableau are useful but understand what you are plotting!! I remember how hard it was as a student to understand why I could not list the bizillion experiments done to answer a research question (my thesis advisor should go to heaven).
  • Comminication: practice structuring data-driven arguments.

scientific publications

You can find some of my academic research here: Publications - research

recent challenges

During the summer 2020, I decided to change carrer path and, in the process, to challenge myself

  • 6/30 Challenge: ran 6 miles every day for 30 days mid July- mig August 2020, feel free to check me on Strava
  • 4x4x48 Challenge: ran 48 miles in 48h (4miles every 4h) Dec 2020. More info check David Goggins 4x4x48 Challenge
  • CS50: took CS50 , which I recommend to gain a good foundation if you are not comming from CS
  • 1,000 miles Challenge in 2020: by end of December I had 1,045 miles
  • Reading Challenge: read at least three books per month
  • Patience Challenge: be patient with my kids (by far the hardest!)
  • ... and I am working on consolidating machine learning

... practice makes PROGRESS!