These are just some links which go into a bit more detail about the things we’ve been looking at the past few days, along with resources which address the most common questions.
I want to learn more python: That is great. There is mulitple good resources out there:
- Datacamp: https://www.datacamp.com/
- I also recommend this course (Sadly the video are in Danish, but the rest of the material is English)
- A lot of this workshop is also modelled after the software carpentry courses. You can see the full list of lessons here:
UCloud official user guide and documentation
- If you have problems setting something up or want to get more info, check the docs first. Link
How do I get a handle of Python basics?
- Check out this free online book which contains a whole bunch of really nice, practical exercises (with solutions!) Link
- A slightly more advanced intro which focuses more on using numpy and matplotlib, finally ending with Python scripting. (Our workshops borrowed material from this course, and radically compressed it). Link
The basic Python “data science” stack
- Links to documentation for the main Python data science tools that we’ve been working with in this workshop. Get used to them! pandas numpy matplotlib scipy
- One more that we didn’t look at is scikit-learn which features core machine learning algorithms. We’ll come back to this another day. scikit-learn
A visual intro to numpy arrays
- Great intro to how arrays work, with fantastic visuals that make it all a bit clearer. (For the record, we’ll be seeing more of Jay Alammar’s visualisations later in the semester during NLP!) Link
Why write .py scripts rather than just use Notebooks?
- A blog post on Medium where the author discusses some of the benefits (open in private/incognito if you get a paywall) Link
- A comment thread on the subreddit r/MachineLearning with different perspectives Link
What does if name == "main" actually do? Why do we need it?
- A really nice discussion of this on StackOverflow; the top answer is one of the best explanations I’ve come across Link