Machine Learning Guides
developers.google.com
Machine Learning Guides
1–10 of 56 posts
Re: Machine Learning Guides
#2Daily reminder for data scientist and machine learning types: fill your pockets while you can, because machine learning bootcamps are on the horizon!
Re: Machine Learning Guides
#3These guides also give good heuristics on how to look at data before throwing a model at it, and deciding what's the most logical model approach/architecture.
A good example is the text preprocessing flowchart (also shared by fchollet on Twitter): https://developers.google.com/machine-learning/guides/text-c...
Re: Machine Learning Guides
#4Daily reminder for data scientist and machine learning types: fill your pockets while you can, because machine learning bootcamps are on the horizon!
There's been data science/machine learning bootcamps around for awhile (Galvanize/Metis being common examples in San Francisco), but apparently job placement is not in a good place (as with normal bootcamps).
Indeed Machine Learning/Deep Learning has become much more accessible thanks to the number of free guides such as this. But that means data science job placement will become more difficult as competition increases, with more gatekeeping/requirements (e.g. Masters/Ph.Ds)
Re: Machine Learning Guides
#5Deep learning and blockchain noise seems to be dying out slowly. Are we going downhill on the hype curve, is it time to short those buzzwords?
Re: Machine Learning Guides
#6Deep learning and blockchain noise seems to be dying out slowly. Are we going downhill on the hype curve, is it time to short those buzzwords?
Yep. The plebs are onto us. Time for a crash ;)
Re: Machine Learning Guides
#7Daily reminder for data scientist and machine learning types: fill your pockets while you can, because machine learning bootcamps are on the horizon!
Yes, deep learning is what web-development was twenty years ago (and now everybody and their mother can build a website).
Re: Machine Learning Guides
#8Daily reminder for data scientist and machine learning types: fill your pockets while you can, because machine learning bootcamps are on the horizon!
Yes, deep learning is what web-development was twenty years ago (and now everybody and their mother can build a website).
Too bad ML as a service is already largely cornered by $FANG
Re: Machine Learning Guides
#9These guides also give good heuristics on how to look at data before throwing a model at it, and deciding what's the most logical model approach/architecture. A good example is the text preprocessing flowchart (also shared by fchollet on Twitter): https://developers.google.com/machine-learning/guides/text-c...
This is something that's almost always glossed over and I'm glad they included it. It's easy to apply ML algorithms to perfect data that doesn't need cleaning and get great results. Finding a productive model when presented with a nuanced, messy problem is a much more difficult task, however, and something most ML crash courses don't focus enough time on.
I think there's a tendency on Hacker News and other tech websites to diminish the importance of having a PhD in ML fields. The problem solving and communication skills you learn during the course of a PhD program are precisely the skills companies value when they're trying to solve hard problems. It's important to know not just how to apply ML algorithms, but when they're appropriate.
Re: Machine Learning Guides
#10Daily reminder for data scientist and machine learning types: fill your pockets while you can, because machine learning bootcamps are on the horizon!
Honestly, unless these ML bootcamps are extensive courses on calculus, linear algebra, and statistics and not just "Here's k-means. Memorize it" I doubt they'll harm the market for grad school educated data scientists.