3 ms·

"I can't come up with any problems that I couldn't solve with a relational database (postgres) and a data transformation step" do it anyway with Machine Learni

"I can't come up with any problems that I couldn't solve with a relational database (postgres) and a data transformation step" do it anyway with Machine Learning and see how it goes. at least you will know the expected results.

mrweasel 8y ago
That will only make those systems hard to understand for other developers and the company isn’t in the business of entertaining a single developers ML fantasies. I get the machine learning is interesting to some people, and it certainly has its place, but applying needlessly complex solutions to simple problems is how software developers get a bad reputation. If you don’t have the need don’t use: ML / AI / Cloud computing / Hadoop / or any other random technology.
- jfoutz 8y ago
  On the other hand, if you don’t build something with it, it’s hard to tell when to apply the tool. I personally have to build some things that turn out to be the wrong approach so I really understand how to build the right thing later. Some small problem that could be replaced is a great opportunity to really understand the solution space ml offers. It really boils down to how important people are to your organization. There is a spectrum between cog and irreplaceable, sometimes growing people is totally worth the cost.
  - maxxxxx 8y ago
    Exactly. Trying out new things in small projects prepares you for bigger things and it goes wrong nothing is list. A lot of failed projects come from jumping into something new with one big step.
- maxxxxx 8y ago
  If it's a relatively simple thing I think it's a good opportunity to try out something new and see how it goes. If it doesn't work out there is not much lost and if it works out you are prepared for bigger things. I think it can be a mistake to do new things only when you really need them.

3 ms·

"I can't come up with any problems that I couldn't solve with a relational database (postgres) and a data transformation step" do it anyway with Machine Learni

by maxxxxx 8y ago

mrweasel 8y ago
That will only make those systems hard to understand for other developers and the company isn’t in the business of entertaining a single developers ML fantasies. I get the machine learning is interesting to some people, and it certainly has its place, but applying needlessly complex solutions to simple problems is how software developers get a bad reputation. If you don’t have the need don’t use: ML / AI / Cloud computing / Hadoop / or any other random technology.
- jfoutz 8y ago
  On the other hand, if you don’t build something with it, it’s hard to tell when to apply the tool. I personally have to build some things that turn out to be the wrong approach so I really understand how to build the right thing later. Some small problem that could be replaced is a great opportunity to really understand the solution space ml offers. It really boils down to how important people are to your organization. There is a spectrum between cog and irreplaceable, sometimes growing people is totally worth the cost.
  - maxxxxx 8y ago
    Exactly. Trying out new things in small projects prepares you for bigger things and it goes wrong nothing is list. A lot of failed projects come from jumping into something new with one big step.
- maxxxxx 8y ago
  If it's a relatively simple thing I think it's a good opportunity to try out something new and see how it goes. If it doesn't work out there is not much lost and if it works out you are prepared for bigger things. I think it can be a mistake to do new things only when you really need them.