Title: I am interested to know what ML platforms you use for personal&#x2F;hobbyist projects... Do you rent GPU instances from the likes of Azure, GCP, AWS or do you use managed solutions like Paperspace Gradient, or Colab? why or not?<p>I am very much a beginner in the space of machine learning and have been overwhelmed by the choices available. Eventually I do want to simply want to build my own rig and just train models on that, but I don&#x27;t have that kind of money right now, nor is it easy to find GPUs even if could afford them.<p>So I am basically stuck to cloud solutions for now, which is why I want to hear personal experiences of HN folks who have used any of the available ML platforms. Their benefits, short comings, which are more beginner friendly, cost effective, etc<p>I am also not opposed to configuring environments myself rather than using managed solutions (such as Gradient) if it is more cost effective to do so, or affords better reliability &#x2F;&#x2F; better than average resource availability... because I read some complaints that Colab has poor GPU availability since shared among subscribers, and that the more you use it the less time is allocated to you... not sure how big of a problem it actually is though.<p>I am very motivated to delve into this space (it&#x27;s been on my mind a while) and I want to do it right, which is why I am asking for personal experiences on this forum given that there is a very healthy mix of technology hobbyists as well as professionals on HN, of which the opinion of both is equally valuable to me for different reasons.<p>Also please feel free to include any unsolicited advice such as learning resources, anecdotes, etc,<p>Thanks for reading until the end.
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