Mono VS tensorflow

In the video you basically install .NET 7.0 SDK with the deb packages from Microsoft repos AND mono deb packages from repos laid out in https://www.mono-project.com/ apart from Unity and VS Code. And then you configure VS Code so that it always uses Mono installed in the system (not Unity Editor's own instance???)

4- Any user-side telemetry would be in the MS .Net framework, which is not used when you selfhost as .net based stuff like Jellyfin use Mono, which is fully open-source and independent (https://www.mono-project.com/)

Did they intentionally name it after a widely used, well known programming framework[1], or did they want to guarantee, I dunno, that they will fly way, way under the radar? I thought it was bad form to name a new programming language 'Cedar', but at least the other Cedar isn't actively developed, unlike the other Mono.

[1] https://www.mono-project.com/ for the few of you who didn't know.

.NET 4.8.1 and earlier do not install on Linux. Unless you want to play around with Mono (your mileage may vary): https://www.mono-project.com/

They have deceived you. https://www.mono-project.com/ I seriously don't know how well wine can deal with newer .NET winforms

It also gained a lot of more popularity and success after the release of the open source implementation of it called Mono.

Hey, I'm working on a C++ game engine in VS Code and wanted to add C# scripting, so I'm trying to install Mono. I already got SDL2 working with CMake, but I'm having trouble setting up Mono because it doesn't seem to have any out of the box CMake support.

Microsoft already has universal cross flatform low level spyware as C# and .NET (which is used by tons of even native linux games, especially made with Unity), mono is sponsored by Microsoft and has telemetry. Wine also uses mono.

And then installs proprietary steam, spotify, vscode and develops on C# for linux with telemetry even in mono runtime...

To get up to speed with TensorFlow, check their quickstart Support TensorFlow on GitHub ⭐

Explore here.

Part of the major userbase pull in GitHub revolves around hosting a considerable number of popular projects including Angular, React, Kubernetes, cpython, Ruby, tensorflow, and well even the software that powers this site Forem.

Right but that's not an inherent GPU determinism issue. It's a software issue.

https://github.com/tensorflow/tensorflow/issues/3103#issueco... is correct that it's not necessary, it's a choice.

Your line of reasoning appears to be "GPUs are inherently non-deterministic don't be quick to judge someone's code" which as far as I can tell is dead wrong.

Admittedly there are some cases and instructions that may result in non-determinism but they are inherently necessary. The author should thinking carefully before introducing non-determinism. There are many scenarios where it is irrelevant, but ultimately the issue we are discussing here isn't the GPU's fault.

and things like y = layers.ELU()(y) work as expected. I wanted to see a list of the available layers so I went to the Tensorflow GitHub repository and to the keras directory. There's a warning in that directory that says:

Exactly what language do you think TensorFlow is written in? :)

You can use Tensorflow's deep learning API for this.

Since you've specifically mentioned ML, here's Tenserflow's GitHub. I'm sure a quick glance through that will change your mind.