(Re)Starting ML & DL Journey

Inspired from @radek’s thread of sharing his new discoveries in thread, I want to start my own thread to share what I learn by (re)visiting the part 1 DL and ML Lectures.

I was lucky to get into the Fellowship but I was conservative with the AWS Credits.
Now that I’ve a Setup in place, I’d love to spend a lot more time on the course and library.

Here’s what I’ll be doing and updating this thread: Putting a hold on Part2, starting again right from the First Lectures.

  • Re-creating the solutions presented by Jeremy strictly WITHOUT Cheating/peeking.
  • Finding similar kaggle competitions to try them.
  • Blogging about new concepts

I also want to help anyone who is struggling with Compute power, Please feel free to reach out. I’d be happy to run your models.




Windows 10 + Ubuntu Dual Boot

  • Disable Secure Boot
  • Disable Fast Boot
  • Change to Legacy boot in BIOS
  • Install ubuntu via a Thumb Drive.
  • Setting up Cuda. Cudnn: @Ekami’s blog posts: Part1, Part 2

Ur Awesome … Dude…:smiley:

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I’m speeding through Machine Learning For Coders right now and I’m starting to believe that ML isn’t witchcraft and the spells can actually be learnt.

I’ve taken a public oath, stolen radek’s classic pledge words (I hope you don’t mind) to start my ML (And If I dare-DL) Path.

I think I’m ready to do a 100 Days of Twitter challenge. To Tweet 1 interesting ML/DL idea/trick that is cool. Everyday for the next 100 days without fail starting today.
I hope I don’t do too bad and really try to find some hidden gems.