21–30 of 99 posts
Is there a decent introduction to scala as a language with real world ML? I've come across various ML primers that go into detail on PCA, Linear regression, etc. But not any that show real world ML usage i.e. if person listen to music of type X they'll also like Y. Face detection, etc.
Is there a decent introduction to scala as a language with real world ML? I've come across various ML primers that go into detail on PCA, Linear regression, etc. But not any that show real world ML usage i.e. if person listen to music of type X they'll also like Y. Face detection, etc.
You also don't see things about feature engineering, how to know what to do next to improve things, etc. ML is an art, and nobody covers this much :(
Java and Scala? Who uses that in ML? Python has long been the best language for ML, with some competition from Matlab.
Java and Scala? Who uses that in ML? Python has long been the best language for ML You're kidding, right? Java has been extremely popular for ML for a long time. Not to cast any shade on Python, but I'd say Java and Python are roughly equivalent in this regard. Both have good libraries for various ML tasks and both are very popular in the domain. For reference, a quick search on mloss.org finds 84 projects identified…
Is anyone else at least a bit worried about a bunch of developers running around doing "machine learning" without much understanding of mathematics and probability? E.g. consider the creation of fragile models that overfit data being used in finance, infrastructure, medicine, etc.
Realistically, the outcome will be the same as it is now: those firms whose models don't reflect reality will blow up, those whose do will get bigger, a few will get too big to fail off some very confidently-expressed models and make a lot of people mad at them, and eventually the market will straighten out who's lying and who's not. Won't be painless, but then, capitalism never is.
Is anyone else at least a bit worried about a bunch of developers running around doing "machine learning" without much understanding of mathematics and probability? E.g. consider the creation of fragile models that overfit data being used in finance, infrastructure, medicine, etc.
Java and Scala? Who uses that in ML? Python has long been the best language for ML, with some competition from Matlab.
Python isn't used for much ML in the field from my experience. It is heavily used for teaching and learning about ML - but for actual production ML, I've seen mostly compiled languages. The main reason is that ML is highly parallelizable and Python isn't terribly good at that. Plus you need to crunch large datasets and speed becomes important. So, respectfully, lots of people use languages other than Python for ML, a…
Most ML is an iterative process, and the final model that's used in production is just the tip of the iceberg of the development work that went on. Python works as well for exploratory programming there as it does for any other domain.
Java and Scala? Who uses that in ML? Python has long been the best language for ML, with some competition from Matlab.
Python isn't used for much ML in the field from my experience. It is heavily used for teaching and learning about ML - but for actual production ML, I've seen mostly compiled languages. The main reason is that ML is highly parallelizable and Python isn't terribly good at that. Plus you need to crunch large datasets and speed becomes important. So, respectfully, lots of people use languages other than Python for ML, a…
Is anyone else at least a bit worried about a bunch of developers running around doing "machine learning" without much understanding of mathematics and probability? E.g. consider the creation of fragile models that overfit data being used in finance, infrastructure, medicine, etc.