Reading through Pandas documentation to work out a problem. I like it when code doesn’t work – sometimes!
Posting this a day late. Took a detour into a course on Pluralsite about the Apollo 11 codebase. It’s an absolute delight, and only takes 30 minutes to view! Heres the link:
Finished the first chapter of #DataCamp’s course: Data Science Toolbox Part 2. Its a free chapter with exercises using iterators and iterables in #Python. I’ve been looking at a few other courses also, to decide what to work on next. I’ve a few options:
- Udacity’s Secure and Private AI scholarship
- Kaggle’s Intro to Machine Learning
- fast.ai’s Practical Deep Learning for Coders
They’re all free, and well supported by online communities ( I earned a scholarship challenge with Udacity, so I can access the scholarship #Slack channel). I’ll have a think about it today, and make decision on what course to give my best effort. Any suggestions?
Python iterators revision with #DataCamp – 1 hour + this morning. I took a leap with the Deep Learning with PyTorch course, and I’m giving that a rest today.
Completed chapter 2 of Deep Learning with PyTorch. This.stuff.is.hard!
Another late post – long shift at work, so reading over a PyTorch tutorial to see if my brain is taking it in!
This post is a day late. Busy traveling to Dublin and back yesterday – used the #DataCamp mobile app for Python practice on the road.
#DataCamp: Deep Learning with PyTorch – Loss Functions. This stuff is really advanced, but I’m starting to grasp the concepts. I’ll keep going with this chapter, as I’m 60% there.
Reading #PyTorch documentation today. That counts, I reckon🤓