Support Becoming a Data Scientist!

I want to hire some people to help me update my websites more frequently, do the maintenance stuff, and to help edit the podcast so I can produce episodes more frequently. I outlined my whole plan here on my Patreon Campaign. You’ll see a new page on this site soon acknowledging supporters, and I’ll update… Continue reading Support Becoming a Data Scientist!

Data Science Learning Club

I’m working on the last of my recording and editing for “Episode 0” of the new Becoming A Data Scientist Podcast, which I’m planning to launch tomorrow! I’ve already recorded the interviews for episodes 1-3, which will be airing over the next month or so – so exciting! The guests all had interesting and informative things to share, I believe you’ll like it a lot.

At the end of each podcast episode, I’ll be “assigning” a “Learning Activity” for the Data Science Learning Club.

A Challenge to Data Scientists

As data scientists, we are aware that bias exists in the world. We read up on stories about how cognitive biases can affect decision-making. We know that, for instance, a resume with a white-sounding name will receive a different response than the same resume with a black-sounding name, and that writers of performance reviews use different language to describe contributions by women and men in the workplace. We read stories in the news about ageism in healthcare and racism in mortgage lending.
Data scientists are problem solvers at heart, and we love our data and our algorithms that sometimes seem to work like magic, so we may be inclined to try to solve these problems stemming from human bias by turning the decisions over to machines. Most people seem to believe that machines are less biased and more pure in their decision-making – that the data tells the truth, that the machines won’t discriminate.

“Becoming a Data Scientist” Learning Club?

I have been thinking about doing a “Becoming a Data Scientist” podcast for a long time, at least since April. The podcast would include interviews focused on how people working in various data-science-related jobs got to where they are today (how did they “become a data scientist”?). I’m getting closer to taking the dive and getting it started.

I had an idea today that would take it a step further. Imagine how book clubs work where you pick a book, go off and read it, then gather occasionally to discuss and record your thoughts. Except instead of a book club, it’s a data science learning club!

How To Use Twitter to Learn Data Science (or anything)

When I decided that I wanted to become a data scientist, I started following some data scientists on twitter to see what they talk about and what was going on in the “industry”. Then I saw them pointing one another at resources, and answering each other’s questions, and I realized I had only seen the tip of the iceberg of “Data Science Twitter”. That’s when I created a new twitter account.

DataSciGuide Update

I finally had a chance this weekend to make some progress on my “Data Science Directory” website, DataSciGuide.com, and I would love your feedback on it! That site isn’t open for comments yet, so I’m directing people to leave feedback here. If you haven’t kept up with the development of DataSciGuide, here are a few… Continue reading DataSciGuide Update

The Imitation Game, and the Human Element in Data Science

Last night, my husband and I watched The Imitation Game. First of all, it’s a great movie and you should see it. Secondly, there was a moment that got me thinking about the human element of machine learning.

[Spoiler Alerts – but you probably already know much of the story, and the movie is still good even if you know the historical outcome.]

I thought a moment like this may be coming when Alan Turing was first applying to work at Bletchley Park, and Denniston can’t believe he’s applying to be a Nazi codebreaker without even knowing how to speak German. Alan emphasizes that he is masterful at games and solving puzzles, and that the Nazi Enigma machine is a puzzle he wants to solve. He starts designing and building a machine that will theoretically be able to decode the Nazi radio transmissions, but the decoder settings change every day at 12am, so the machine must solve for the settings before the stroke of midnight every day in order for the day’s messages to be decoded in time to be useful and not interfere with the next day’s decoding process. Turing can’t prove his machine will work, simply because it is simply taking too long to solve the daily puzzle. In the meantime, people are dying in the war, and the Nazis are going on transmitting their messages over normal radio waves believing the code is “unbreakable”.