Personally I stick with the classic SMLNJ
Ask HN: What ML platform are you using?
11–20 of 84 posts
Re: Ask HN: What ML platform are you using?
#12You can run on-demand training jobs on GCP vertex ai training. I'm not sure the price point but it's pretty useful both for development and training.
Re: Ask HN: What ML platform are you using?
#13Are you just interested in the training part and managing the trained models, or you'd actually like to productionize the models and serve them at scale?
A lot of end-to-end platforms are available nowadays that try to cover the entire lifecycle of a model from data prep, ETL, to training, serving, monitoring, operating. However, I found none of them really robust enough to cover all these cases perfectly, so I resorted to using different pieces from different vendors combined with my own stuff to make the entire platform suit my needs. This is still not perfect, though, and I think there's a lot of room for improvement in the space to enable really easy to use and scalable MLOps.
Still some of the tools I found to be ok: TensorFlow TFX, Kubeflow (to some extent - ops are a nightmare), Feast, MLFlow, GCP Vertex and AWS Sagemaker can get some work done, too.
Re: Ask HN: What ML platform are you using?
#14Get a decent NVIDIA GPU. Then install PyTorch and off you go. I advise to make all your own tooling, as you likely have a specific use-case, and so your tooling can be tailored to that. Most ML tools are very generic, or so simply you might as well do them yourself.
The advantage if having your own box, is that (1) you'll learn some systems skills building it and (2) since you invested in it, you should feel obligated to use it! Good luck.
Re: Ask HN: What ML platform are you using?
#15I put together a linux box with a 2080ti a few years ago and have been using it consistently for personal ml research ever since. Ive found it well worth the investment and learned that the ease with which I can jump into hacking on a project is key, which is why this works so well for me. I can just ssh in at any time and start experimenting with models. Even if its not technically economical when you do the math, the ease, reliability and fact that I know my models arent being billed per hour helps encourage me to experiment often, which is kwy to learning.
As for software, I do everything with jax and tensorboard for viewing experiments. Jax is a phenomenal library for personal ml learning as its extremely flexible and has relatively low level composable abstractions.
Re: Ask HN: What ML platform are you using?
#16Thr best option for you is- Gradient Paperspace and Colab. Both are free and managed.
Learn Machine Learning first. Do not spend time on managing infra for ML while you are learning ML. Focus on learning ML first.
You can make decent cutting edge models and SOTA classic models just with free options. I am saying this because I have done this.
I suggest that you get Colab Pro after that.
AWS burns a hole on your pocket, and you should not spend money on that now. Although, AWS SageMaker is pretty tension-free experience.
I personally use GCP. I like the tooling around it to be the most convenient.
I suggest you learn the basics first. Learn classic ML, CNNs, RNNs, LSTM, Transformers, learn the necessary Maths, and even GANs if you are inclined.
If done in the right way, it will take you a 5/6 months to 18/20 months, depending on your time commitment, your current levels of grasp on programming and Math.
Do not rush or hurry.
When you reach that point, you can think of spending serious money for Deep Learning projects.
A few months back, I have gotten into TPUs, and these are fantastic. And GCP is my only option for these. I have only used TPUs for learning and personal project and never for work. I intend to keep it that way for a while.
Re: Ask HN: What ML platform are you using?
#17Thr best option for you is- Gradient Paperspace and Colab. Both are free and managed. Learn Machine Learning first. Do not spend time on managing infra for ML while you are learning ML. Focus on learning ML first. You can make decent cutting edge models and SOTA classic models just with free options. I am saying this because I have done this. I suggest that you get Colab Pro after that. AWS burns a hole on your pocke…
can you please be specific on "necessary Math"? trying to apply pareto principle and cut down amount of time needed to brush up what seemingly all of lower division math courses.
Re: Ask HN: What ML platform are you using?
#18I recommend to use Colab for learning because so many research papers publish their own examples as a Colab link nowadays, so you'll have plenty of stuff to try out and explore.
For the actual deployment in production, the only thing that's really affordable is if you send your own GPU workstations to a colocation hosting company. But that's a lot of work.
Re: Ask HN: What ML platform are you using?
#19Get a decent NVIDIA GPU. Then install PyTorch and off you go. I advise to make all your own tooling, as you likely have a specific use-case, and so your tooling can be tailored to that. Most ML tools are very generic, or so simply you might as well do them yourself. The advantage if having your own box, is that (1) you'll learn some systems skills building it and (2) since you invested in it, you should feel obligate…
And you can run your own github/gitlab runner on the GPU box and set up CI in your projects. It's good practice (and good practise). And it's free. This unchains you from your PC so you can push code from anywhere and it'll crunch the numbers for you. You just need to install docker, run the runner and make sure you're using a runner container with the NVIDIA stuff installed and you pass through the GPU to the container.
Re: Ask HN: What ML platform are you using?
#20I created something that lets you get free GPU on VS Code with Google Colab with just 1-click. Have a look at https://github.com/DerekChia/colab-vscode
This is my default go-to as a poor man ML setup, with environment and dependencies set up automatically via bash script on start up.