This is the fourth in a series on The Basics of Organizing For Data Science. In this series: Why Agendas; Why Prepare For A Meeting; Why Document A Meeting; Why The [ACTION REQUIRED] email tag; Why The Bullet Point. Why The [ACTION REQUIRED] email tag in the subject line Because you are calling out that an action is required; Because you are calling out that a specific email is important; Because clarity is more likely to cause action; Because it is not always clear which emails are important and which are not important. Where to use [ACTION REQUIRED] In the subject line of an email. What is [ACTION REQUIRED] The Addressee is asked to undertake an action that is important,[…]

This is the fifth in a series on The Basics of Organizing For Data Science. In this series: Why Agendas; Why Prepare For A Meeting; Why Document A Meeting; Why The [ACTION REQUIRED] email tag; Why The Bullet Point. Why The Bullet Point Because they’re readable; Because they’re short; Because readable and short things are more likely to be read. What Is The Bullet Point <—- This right here; It’s sometimes it’s used as an item in an unordered list of items; The line has blurred between the ordered list and the unordered list. Where To Use The Bullet Point In powerpoint presentations; In email; In blog posts about bullet points. When To Use The Bullet Point When you want[…]

This is the third in a series on The Basics of Organizing For Data Science. In this series: Why Agendas; Why Prepare For A Meeting; Why Document A Meeting; Why The [ACTION REQUIRED] email tag; Why The Bullet Point. Why Document A Meeting Because data is getting generated by people; Because data is getting organized or disorganized; Because the probability of full quorum approaches 0 as the number of participants increases to 12 and beyond; Because decisions are at their clearest when they are documented and circulated; Because those that come after you can trace the intuition for a decision. Which Meetings To Document Meetings with a strong decision component should be documented; Meetings with a very strong situational awareness[…]

There’s a quote from The Office (US) [Season 6, episodes 5/6, “Launch Party”]: Michael: Okay, okay, what’s better? A medium amount of good pizza? Or all you can eat of pretty good pizza? All: Medium amount of good pizza. Kevin: Oh no, it’s bad. It’s real bad. It’s like eating a hot circle of garbage. The launch in that episode was the ill fated “Dunder Mifflin Infinity”, and while the reference in the passage is to the pizza that Michael Scott had ordered, it may as well been referring to the website. For many reasons, people tend to build all you can eat hot circles of garbage, instead of a medium amount of pretty good pizza. Minimum Viable Product and[…]

Do you like new technology? Chances are that if you’re reading this space, you do. I like new technology too. I don’t like hype as much. I get suspicious when people go out of their way to inflate expectations deliberately in advance of a promise that they know, full well, it can’t deliver. Whether you’re buying for yourself, your home, or your organization, you want to invest in technology that’s likely to have a return, but not such a diminished return that you derive absolutely no competitive advantage or learning from it. There’s a balance there between the fear of losing too much and the greed of unfair advantage. To understand why these feeling develop, it helps to understand why[…]

You may have been to a conference. Ever wonder why they’re the way they are? The Conference Market(s) Different people hire a conference to do different jobs. For some, a conference is a chance to learn, be exposed to new ideas, and exit a comfort zone. Or, to enter a comfort zone to be exposed to new ideas and feel safe enough to learn. For some, it’s entirely about networking with colleagues, or recruiting, or to be recruited. For others, a conference is a chance to spam people with signing authority with their marketing messages. Or to upsell. Or to crossell. Or to retain. For others still, a conference is a reason to visit a city. To get the hell[…]

Backcasting is a fantastic technique. It was invented in Canada. You’re welcome to use it. If it sounds like forecasting – well – that’s because it’s kind of like forecasting. With an important difference. That wikipedia page says: Whereas forecasting is predicting the future (unknown) values of the dependent variables based on known values of the independent variable, backcasting can be considered the prediction of the unknown values of the independent variables that might have existed to explain the known values of the dependent variable. I had to re-read it a few times to really get it. Once you get it, it’s just elegant. What’s beautiful is that it can silence the reactive-pure-statistician brain long enough for the prospective centre of the creative brain to imagine several futures. What I like about backcasting[…]

I was 28 and sleepless when I encountered a marketing version of the logistic function. It was beautiful. It’s one of those things you’re taught about in one context, and when you’re shown it from another angle, it expands your mind. It was like discovering Pi for the first time. I could use it to check the assumptions of a market penetration forecast, and substitute my own estimates for others. I felt empowered and delirious from being able to produce a solid forecast. It became a tool as useful as btau or the crosstab. There’s a part of that math, a variable called saturation, that worried me from the outset. Saturation is the maximum percentage of adoption that a market[…]

Jon Evans wrote a piece for Techcrunch entitled: After the end of the startup era. In it, Evans writes: We live in a new world now, and it favors the big, not the small. The pendulum has already begun to swing back. Big businesses and executives, rather than startups and entrepreneurs, will own the next decade; today’s graduates are much more likely to work for Mark Zuckerberg than follow in his footsteps. And, Because we’ve all lived through back-to-back massive worldwide hardware revolutions — the growth of the Internet, and the adoption of smartphones — we erroneously assume another one is around the corner, and once again, a few kids in a garage can write a little software to take[…]

It was a treat to see these three – Yoshua Bengio, Yann Lecun, and Geoffrey Hinton – for an afternoon. Easily the best three consecutive hours I’ve ever seen at a conference. They remarked that Canada continues to invest in primary research. And this is a strength. Much of the exploratory work these three executed in the 80’s, 90’s and naughties was foundational to industrial applications which came after. Much of reinforcement and deep learning has moved on into industrial application. For the three grandfathers of deep learning, all of these algorithms and methods move into the realm of solved problems. For those of us in industry, there remains a lot of work to realize the benefits of deep learning.[…]