I can’t elaborate yet, but in case you wondered how scientific satisfaction looks like, here’s a perfect illustration.

Stay tuned
Data Science & Communication Consultant and Advisor | AI, Machine Learning, Data Visualization
I can’t elaborate yet, but in case you wondered how scientific satisfaction looks like, here’s a perfect illustration.
Stay tuned
Is Data Science a Science? I think that there is no data scientist who doesn’t ask his- or herself this question once in a while. I recalled this question today when I watched a fascinating lecture “Theory, Prediction, Observation” made by Richard Feynman in 1964. For those who don’t know, Richard Feynman was a physicist who won the Nobel Prize, and who is considered one of the greatest explainers. In that particular lecture, Prof. Feynman talked about science as a sequence of Guess ⟶ Compute Consequences ⟶ Compare to Experiment
This is exactly what we do when we build models: we first guess what the model should be, compute the consequences (i.e. fit the parameters). Finally, we evaluate our models against observations.
My favorite quote from that lecture is
… and therefore, experiment produces troubles, every once in a while …
I strongly recommend watching this lecture. It’s one hour long, so if you don’t have time, you may listen to it while commuting. Feynman is so clear, you can get most of the information by ear only.