A reason to use feature flag third party services is for the analytics and insights into the user behaviour. Such services cost a lot but might be worth it if you don't have the resources to build such an infrastructure.
Which game you play is certainly a factor. If you like composing original music that may be a game worth playing even if the odds are no better than an actual lottery.
Not really. You still have to do that last step, the one that gets you ahead, yourself. Thats the step we're talking about.
There is a very real issue here imho, for the Anglo-sphere (the EU seems much better at this, full disclosure, im a brit but i think the us and uk are the ssme in this). We don't invest and increasingly we're not competitive. Cisco dropped the ball, Huawei picked it up. Maybe every previous step was stolen, but that's the step that have given Huawei their success. They have an advantage because no one else is making a comparable product.
As long as we just complain and blindly insist the chinese are cheating, we won't address the actual issues that are really holding us back.
The chinese are investing in education? Maybe we should. The chinese force their companies to take a view past the next quarter profit report? Maybe we should. If whatever their advantage is, its not stealing (not anymore at least) and until we address it, we will be whining and they will be winning.
Guess it works with having a base image and just rebuilding it with the code that should be run. Code is passed via an api call from frontend to backend. This should make sure not the whole environment is rebuilt again because of the docker cache but only the code which has been submitted.
How the docker thing actually works is just my guess btw.
This brings back so many memories from around 17 years ago when I would try to do a dual install of arch linux with windows XP using the GRUB bootloader. Fun times! Can't believe it's been so long!
as someone new to ML/DL where can I get started? would you recommend the Fast AI course using pytorch based libraries or something else that focuses on tensorflow?
The key is to find something you think is fun, and play with it. It doesn’t matter what it’s written in. I don’t think it would be fun to take a course, so I never did. But it was a blast to get all this working: https://youtube.com/channel/UCqpwMaJbb-zj-MlMkRd28QQ
You can see my early videos were crude meme attempts, and eventually it morphed to 100 TPU training. You can’t really predict the things that you’ll like, so don’t try.
What’s fun to you? That’s the question to focus on. For me, it was language modeling and image generation, which I learned from https://gwern.net/GPT-2 and Peter Baylor’s’ stylegan notebook, respectively. Then I transitioned to audio memes https://youtu.be/koU3L7WBz_s and kept going from there.
Tensorflow is bullshit, pytorch is different bullshit, Jax is pretty friggin awesome but still has one or two flecks of bs. But none of it feels hard to deal with, because it’s all an enormous box of legos; as long as you chase your interests, you’ll never* feel like it’s annoying.
* you’ll be annoyed all the time, but at least you’ll keep going.