Analyzing electric utility data using machine learning • Hacker News Board

Re: Analyzing electric utility data using machine learning

#21

Post by dang » Mon, Mar 27, 2017, 4:52 AM UTC

minimaxir wrote: post #19

dang wrote: post #15

Posting an outrageous title to get attention, thereby triggering a discussion entirely focused on the outrageous title is such an anti-pattern that we've demoted this post. Normally we can find representative language in the body of an article to serve as a substantive title, but I tried and came up empty in this case. That can't be a good sign.

Unfortunately, this type of headline is less clickbaity than other headlines I've seen recently relating to Data Science/Machine Learning, even on Hacker News. (although in this case, the clickbaityness is more deliberate ) It is honestly one of the reasons I am cutting down on producing blog articles on those topics, because I can't compete with clickbait-articles-which-peddle-machine-learning-as-magic-when-it-is-no…

Yes, this genre is well along on the hype curve. We may not always be able to assess when articles are doing this but we're definitely open to suggestions for better (= more accurate and neutral) titles.

Re: Analyzing electric utility data using machine learning

#22

Post by hahaker » Mon, Mar 27, 2017, 5:16 AM UTC

No you didn't recreated anything. That company is worth 500M. Your fun experiment is not.

On the other hand, this is excellent PR for Opower.

Re: Analyzing electric utility data using machine learning

#23

Post by samblr » Mon, Mar 27, 2017, 6:14 AM UTC

Finding problem space in haystack is more important than building solution. Because that would mean founders' know why a solution exists as it exists in problem space and how to mould/pivot it down the line and build company around it.

Re: Analyzing electric utility data using machine learning

#24

Post by gianlucahmd » Mon, Mar 27, 2017, 7:24 AM UTC

Hi guys, I'm the person who wrote the article.

I perfectly know that the title is an exaggeration, but choosing an headline for medium is a tough job :)

The reason why I chose to call it like this, is not just to get a couple of clicks, but because while talking to companies that are not ML-aware I often get the question: "how the hell does X do that?!?!?", and the answer 80% of the time could be 4 lines of sklearn.

My goal is to spread awareness on the potential of ML among companies: my intended audience was not ML engineers, to whom this article looks more like "I spent 6 days cleaning data, 20 minutes plotting different clusters representations, and the rest of the day writing an article", but the business person that is not fully aware of what it means to use ML today, and to whom it looks like something amazing and extremely valuable.

Does it make more sense now? :D

Re: Analyzing electric utility data using machine learning

#25

Post by minimaxir » Mon, Mar 27, 2017, 12:42 PM UTC

gianlucahmd wrote: post #24

Hi guys, I'm the person who wrote the article. I perfectly know that the title is an exaggeration, but choosing an headline for medium is a tough job :) The reason why I chose to call it like this, is not just to get a couple of clicks, but because while talking to companies that are not ML-aware I often get the question: "how the hell does X do that?!?!?", and the answer 80% of the time could be 4 lines of sklearn.…

As the top comment on this post (https://news.ycombinator.com/item?id=13965043) demonstrates, the title is misleading at best, and I do not believe you want to intentionally mislead your readers. Rhetorical smiley faces do not change that.

Keep in mind that clickbait titles do get penalized on Hacker News, as dang notes.

Re: Analyzing electric utility data using machine learning

#26

Post by gianlucahmd » Mon, Mar 27, 2017, 1:32 PM UTC

minimaxir wrote: post #25

gianlucahmd wrote: post #24

Hi guys, I'm the person who wrote the article. I perfectly know that the title is an exaggeration, but choosing an headline for medium is a tough job :) The reason why I chose to call it like this, is not just to get a couple of clicks, but because while talking to companies that are not ML-aware I often get the question: "how the hell does X do that?!?!?", and the answer 80% of the time could be 4 lines of sklearn.…

As the top comment on this post ( https://news.ycombinator.com/item?id=13965043 ) demonstrates, the title is misleading at best , and I do not believe you want to intentionally mislead your readers. Rhetorical smiley faces do not change that. Keep in mind that clickbait titles do get penalized on Hacker News, as dang notes.

I didn't even post it on HN, you guys aren't my target as I explained.

I'm trying to make business execs more eager to experiment ML in their companies, and less afraid about the years of R&D and skynet scenarios they currently relate AI to.

The title was an hyperbole? Yes, but it worked in getting the attention of my target audience. Anyone trying to work as an ML engineer knows that what I did is simple and far from being worth $500M, but should still thank me for spreading awareness on the potential of this technology among who's still scared.

Re: Analyzing electric utility data using machine learning

#27

Post by bpacker » Mon, Mar 27, 2017, 10:17 PM UTC

Ex-Opower Data Scientist here. Cool to see this done. Just wanted to add a link to the Opower blog post describing the original work this was based on, done by Erik Shilts: https://blog.opower.com/2014/10/load-curve-archetypes/.