researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)

	flag.BoolVar(&DebugV, "v", false, "print debug output")
	flag.Var(objabi.NewDebugFlag(&DebugFlags, nil), "d", "enable debugging settings; try -d help")
	objabi.AddVersionFlag() // -V
	objabi.Flagcount("S", "print assembly and machine code", &PrintOut)

	DebugFlags.CompressInstructions = 1
}

// MultiFlag allows setting a value multiple times to collect a list, as in -I=dir1 -I=dir2.
type MultiFlag []string

* 📝 Add external link: Building simple E-Commerce with NuxtJS and FastAPI. PR [#3271](https://github.com/tiangolo/fastapi/pull/3271) by [@ShahriyarR](https://github.com/ShahriyarR).
* 📝 Add external link: Serve a machine learning model using Sklearn, FastAPI and Docker. PR [#2974](https://github.com/tiangolo/fastapi/pull/2974) by [@rodrigo-arenas](https://github.com/rodrigo-arenas).