https://www.tensorflow.org/install/lang_go
понедельник, 28 декабря 2020 г. в 15:01:07 UTC+5, Vitaly: > https://www.tensorflow.org/ > > понедельник, 28 декабря 2020 г. в 11:09:48 UTC+5, meera: > >> I don't know what resources you have tried already so I'm probably going >> to state the obvious. >> >> You're probably looking for some language agnostic resources on the >> subject, since having it be Go specific will narrow your search. >> >> ML like any part of computer science can be described with algorithms, >> data structures and a sprinkle of sorcery. Looking for implementations in >> Go might help, but ultimately you're going to learn from theory, so books >> are a good start. >> >> My bet would be: >> for { // ever >> - Grab a couple of books, read the important bits of each one (textbooks >> also have bloat) >> - Look for easy algorithms and implement them >> } >> >> And don't use magical packages, when magic breaks only the sorcerer can >> patch it up, and you'll be only learning to use the _package_ and not the >> actual ML >> >> >> >> >> >> On Mon, 28 Dec 2020, 00:29 Nikolay Dubina, <nikolay.d...@gmail.com> >> wrote: >> >>> Go does not have much traction in ML and for good reasons: >>> >>> * not a single one organization or company is backing Go ML projects >>> * with exception couple papers, no research in neither computer vision, >>> NLP, or RL is done in Go, no papers are implemented in Go. It is mostly >>> Pytorch these days. >>> * Go language does not support: multi-dimensional indexing; >>> N-dimensional arrays; operator overloading; short lambda notation — all >>> these are loved by data science and machine learning community since it >>> makes life a lot easier for them, but not in Go >>> * Go support for GPU is not good >>> * Go compiler does not support optimizations like SIMD — so even CPU >>> intense workloads are not as performant >>> * Go calls to C can be made, but "cgo is not go" and benefits of Go >>> deteriorate quickly with this approach — so a lot of ML code in C can not >>> be really efficient with Go >>> * Audio / Video / Image / Spatial data is not supported well in Go (just >>> try to run OpenCV in Go, likely it will be either IPC or cgo...) >>> * Many ML related libraries are supported by a single person or already >>> deprecated or highly unstable or experimental >>> >>> Is there way forward? >>> >>> Writing experimentation, data visualization, data wrangling, modeling, >>> training in Go is shooting yourself in the foot. I already tried this >>> myself once for porting Julia code. I would not believe any single DS or ML >>> person would use Go seriously for these purposes. >>> >>> However, there is a niche that Go may fit — tabular data (your backend >>> data model) + inference. Which means, ML model is developed and >>> *trained* in say Python/Julia/R but then ported to Go and loaded >>> trained model artifacts. I recently wrote >>> https://github.com/nikolaydubina/go-featureprocessing as a first step >>> in that direction and more work will follow up. >>> >>> Here is what ML there is in Go at the moment: >>> >>> * https://github.com/josephmisiti/awesome-machine-learning#go >>> * https://github.com/avelino/awesome-go#machine-learning >>> >>> On Monday, December 28, 2020 at 2:11:37 AM UTC+8 ren...@ix.netcom.com >>> wrote: >>> >>>> I think you might be better off learning AI/ML using Python - to >>>> understand the concepts - most tutorials use Python/Colab as well since it >>>> is so easy. >>>> >>>> Once you understand the concepts you can use Go libraries >>>> <https://pkg.go.dev/github.com/tensorflow/tensorflow/tensorflow/go> to >>>> implement the concepts in Go. >>>> >>>> On Dec 27, 2020, at 11:55 AM, Philip Chapman <pcha...@pcsw.us> wrote: >>>> >>>> I am an experienced developer and fairly knowledgeable in Go, but new >>>> to AI and machine learning. I'd like to expand my skillset in that >>>> direction. I would be happy for and recommendations and advice on good >>>> material for learning AI and machine learning with Go. Most of the >>>> material >>>> out there seems to be based on python, but I rather prefer Go. >>>> >>>> -- >>>> You received this message because you are subscribed to the Google >>>> Groups "golang-nuts" group. >>>> To unsubscribe from this group and stop receiving emails from it, send >>>> an email to golang-nuts...@googlegroups.com. >>>> To view this discussion on the web visit >>>> https://groups.google.com/d/msgid/golang-nuts/CABEejsiZMjpTgbZx_7aGRdEcReyHYuk1eNe1WHOdHOdv6jsXFA%40mail.gmail.com >>>> >>>> <https://groups.google.com/d/msgid/golang-nuts/CABEejsiZMjpTgbZx_7aGRdEcReyHYuk1eNe1WHOdHOdv6jsXFA%40mail.gmail.com?utm_medium=email&utm_source=footer> >>>> . >>>> >>>> >>>> -- >>> You received this message because you are subscribed to the Google >>> Groups "golang-nuts" group. >>> To unsubscribe from this group and stop receiving emails from it, send >>> an email to golang-nuts...@googlegroups.com. >>> >> To view this discussion on the web visit >>> https://groups.google.com/d/msgid/golang-nuts/f974314f-7458-4f64-9e94-fed3b850cc51n%40googlegroups.com >>> >>> <https://groups.google.com/d/msgid/golang-nuts/f974314f-7458-4f64-9e94-fed3b850cc51n%40googlegroups.com?utm_medium=email&utm_source=footer> >>> . >>> >> -- You received this message because you are subscribed to the Google Groups "golang-nuts" group. 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