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Throw weka away, it is very bad for actual ML work. use tensorflow, or Spark. Weka is good for research or small scale data sets.
ML has two parts - data domain, and ML algorithem. You need to know the quality of the data, and match the optimal algorithem (or algorithems) to it. -
Brolls31557yI’ve been playing with scikit, but I’m hating python with a passion.
Nice language I’m sure, but the breaking changes and dynamic nature of it basically seems to make people think they have a free pass to switch things up all the time.
Most tutorial code fails to run because it’s all different now, and then having things break at runtime because of a code error really pisses me off.
Machine learning is hard. I’m terrible at maths, so I’m slowly exposing myself to the concepts and playing around with it all. -
Use Keras (if you work with images mostly) or Pytorch (best for Nlp) , when you get more advanced use tensorflow. If you want to do anything with real big data, take a look at BigDL or Spark ML.
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Thanks for all the suggestions. I certainly will try these out, once I've gotten myself out of this mess.
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Senior937yYou should learn the underlying concepts before jumping to any of those super-high abstraction toolsets. Read a book or two of underlaying math and logic. You will thank yourself later.
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