avilay

  1. Distributed Reinforcement Learning with RLLib
  2. Distributed Deep Learning with PyTorch
  3. Reinforcement Learning with PyTorch
  4. Linear Algebra for ML with numpy
  5. Other (please specify)

I like to teach what I learn and have a few tutorials up on YouTube. I need your help in figuring what should I put up next.

Hello HN community - for the past year or so I have been plugging away on a side project called torchutils (https://gitlab.com/avilay/torchutils). It'd be great if you could take it for a spin when training your next ML model and give me some feedback. Here are the detailed docs (https://avilay.gitlab.io/torchutils/)

I am an ML engineer and have my own workflow that I use now and an aspirational workflow that I want to use. But I was curious how other ML engineers make this call. Here are some options to kickstart your thinking: a) Release it if it performs well in offline training b) A/B test in production alongside existing model(s) c) Use contextual bandits in production d) Some other way (details appreciated :-) )

Hello fellow hackers,

Would really appreciate some feedback on a service that I am building that will show a list of your favorite shows and episodes that have recently become available online. It will also recommend shows from across different TV and movies websites.

You can find the service here - http://tvnow.herokuapp.com/

I am trying to scratch a personal itch with this service. A lot of times I find myself searching for shows on different streaming websites without really settling on something to watch. With this service I can now go to one service and see what is available across different streaming websites.

The topmost question in my mind is - apart from me, will anybody else find this useful/interesting? Would love to hear your thoughts on this.

Regards, Avilay