Diary of a Data Scientist - Diary of a Data Scientist
Diary of a Data Scientist

Diary of a Data Scientist

13 Sep

Blog posts like “Reservoir Sampling and Neural Networks for Streaming Data and the IoT” or “Up-Lift Modelling for Cancer Treatments” are interesting and useful to data scientists in particular fields or to particularly creative and savvy readers. However, starting out with esoteric use cases or technical descriptions of specific technologies severely limits the “what,” “why,” and “how” of analysis, if not leaving it out altogether. Leading with current results and building value first is a boon to everyone.

23 Aug

If researchers can’t understand a provided answer, it is not viable.  They can’t write about techniques they don’t understand beyond “Here are the numbers.  Look how pretty my model is.” Good research, that ain’t.

09 Aug

Time Series? Spatial Models? Experimental data? Observational Study? Plunk it right in there.  It’s all the same.

26 Jul

I started to think about the consequences of medical misdiagnoses. What happens if someone has an infection and is told they do not by their doctor? What if someone does not have an infection but is treated as if they do? Which mistake would be worse?


12 Jul

If you search for top skills that data scientists need, you will find communication in the top five or ten in every post, right up there with technical skills...

28 Jun

"My process is very similar to that of any other analyst, so what makes a statistician unique? Our training. Most of a statistician’s training in applied statistics revolves around model building and diagnostics. Some of the things that we care a lot about (trust me, there are a lot more!) are assumptions, bias and variance, model selection, and properly answering questions."

14 Jun

the question of “where is the data?” or “where does this data come from?”

Exploring the world of data mining and the triumphs and challenges experienced first hand from our in-house data scientists.

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