Surviving Data Science at the Speed of Hype
john-foreman.com
Surviving Data Science at the Speed of Hype
1–10 of 48 posts
Re: Surviving Data Science at the Speed of Hype
#2This is perhaps the first halfway sensible post on "big data" or "analytics" that I've seen hit the front page of HN in a long time.
Re: Surviving Data Science at the Speed of Hype
#3Good article. The author is completely correct that people often underestimate the fragility of predictive models, and that summary analysis (I group this into a more general concept called "insights") are simpler and more robust. I think the article is a little harsh towards predictive models though.
The primary difference between a model and an insight is that insights require a human to process - anything more automatic is a model. Insights are easy to implement and are great for finding patterns and anomalies (the human mind is basically designed to pick these out). But the human element makes insights less scalable with significantly higher latency. For some problems these are unacceptable tradeoffs, and this has little to do with how stable a company's environment is. It's purely a product/strategy question, and about understanding all the tradeoffs.
Re: Surviving Data Science at the Speed of Hype
#4Good article. The author is completely correct that people often underestimate the fragility of predictive models, and that summary analysis (I group this into a more general concept called "insights") are simpler and more robust. I think the article is a little harsh towards predictive models though. The primary difference between a model and an insight is that insights require a human to process - anything more aut…
Great to know model/insight difference. You have drawn a clearer line for me, which I always struggled to think it through, even I was quite aware that they are quite different.
Re: Surviving Data Science at the Speed of Hype
#5I just love the way this guy writes. His book, Data Smart, is hands down the most approachable intro to data science you could ever possibly read if you don't have the sufficient math background to dive into full on textbooks. And it's hilarious too.
Re: Surviving Data Science at the Speed of Hype
#6Timely. I did a "big data" presentation yesterday and hoped to convey how important it was to read original source materials to form opinions and avoid the hype.
Since slide decks get busy I moved my bibliography of links to a gist. So, while it didn't factor into my presentation I've now added this blog post. :-)
Re: Surviving Data Science at the Speed of Hype
#7Good point.
Re: Surviving Data Science at the Speed of Hype
#8I just love the way this guy writes. His book, Data Smart, is hands down the most approachable intro to data science you could ever possibly read if you don't have the sufficient math background to dive into full on textbooks. And it's hilarious too.
I have mixed feelings about that book. I enjoyed his writing style and humor, but the amount of beating on Excel he has to do to manipulate all that data hurts my head. I kept thinking of how much easier it would be to do with code.
Maybe it's just not a good book for developers? shrug I would love to have a copy of that book that doesn't use Excel.
Re: Surviving Data Science at the Speed of Hype
#9I just love the way this guy writes. His book, Data Smart, is hands down the most approachable intro to data science you could ever possibly read if you don't have the sufficient math background to dive into full on textbooks. And it's hilarious too.
I have mixed feelings about that book. I enjoyed his writing style and humor, but the amount of beating on Excel he has to do to manipulate all that data hurts my head. I kept thinking of how much easier it would be to do with code. Maybe it's just not a good book for developers? shrug I would love to have a copy of that book that doesn't use Excel.
Write it!
Re: Surviving Data Science at the Speed of Hype
#10I just love the way this guy writes. His book, Data Smart, is hands down the most approachable intro to data science you could ever possibly read if you don't have the sufficient math background to dive into full on textbooks. And it's hilarious too.
I have mixed feelings about that book. I enjoyed his writing style and humor, but the amount of beating on Excel he has to do to manipulate all that data hurts my head. I kept thinking of how much easier it would be to do with code. Maybe it's just not a good book for developers? shrug I would love to have a copy of that book that doesn't use Excel.
I share your same yearning for a code equivalent of the book. However, I think writing the book using only Excel was a smart move on his part, simply because:
1) Excel is "visual" in the sense that you can watch the data change as you tweak things. There is no command line or program to execute, it's all happening live
2) For programmers, there's no "well I'm a python guy and this book is written in Java so it's not for me." None of us as coders really depend on Excel for writing code (basically) so it's kind of a way to take the technology decisions out of the equation. It's just the techniques.
All that being said, it's not trivial to port the logic of a spreadsheet over to code, and I think if anything that would make a great followup book.