$ docker
const admin = require('firebase-admin'); | |
const fs = require('fs'); | |
const serviceAccount = require('../../../../../../Private/myschool-data_transfer-key.json'); | |
admin.initializeApp({ credential: admin.credential.cert(serviceAccount) }); | |
const schema = require('./schema').schema; | |
const firestore2json = (db, schema, current) => { |
This is an incomplete, ever-changing curated list of content to assist people into the worlds of Data Science and Machine Learning. If you have a recommendation for something to add, please let me know. If something isn't here, it doesn't mean I don't recommend it, I just may not have had a chance to review it yet or not.
I will generally list things in order of easier to more formal/challenging content.
It may feel like there is an overwhelming amount of stuff for you to learn (because there is). But, there is a guided path that will get you there in time. You need to focus on Linear Algebra, Calculus, Statistics and probably Python (or R). Your best bet is to get a Safari Books Online account (https://www.safaribooksonline.com) which you may already have access to through school or work. If not, it is a reasonable way to get access to a tremendous number of books and videos.
I'm not saying you will get what you need out of everything here, but I have read/watched at least some of all of the following an
Service | SSL | status | Response Type | Allowed methods | Allowed headers |
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[ Update 2025-03-24: Commenting is disabled permanently. Previous comments are archived at web.archive.org. ]
Most of the terminal emulators auto-detect when a URL appears onscreen and allow to conveniently open them (e.g. via Ctrl+click or Cmd+click, or the right click menu).
It was, however, not possible until now for arbitrary text to point to URLs, just as on webpages.
curl -s https://api.github.com/users/milanboers/repos | grep \"clone_url\" | awk '{print $2}' | sed -e 's/"//g' -e 's/,//g' | xargs -n1 git clone |
# http://webapps.stackexchange.com/questions/39587/view-estimated-size-of-github-repository-before-cloning | |
# tested on macOS | |
echo https://github.com/torvalds/linux.git | perl -ne 'print $1 if m!([^/]+/[^/]+?)(?:\.git)?$!' | xargs -I{} curl -s -k https://api.github.com/repos/'{}' | grep size | |
# output: | |
# "size": 1746294, |
- View: Also called a "template", a file that contains markup (like HTML) and optionally additional instructions on how to generate snippets of HTML, such as text interpolation, loops, conditionals, includes, and so on.
- View engine: Also called a "template library" or "templater", ie. a library that implements view functionality, and potentially also a custom language for specifying it (like Pug does).
- HTML templater: A template library that's designed specifically for generating HTML. It understands document structure and thus can provide useful advanced tools like mixins, as well as more secure output escaping (since it can determine the right escaping approach from the context in which a value is used), but it also means that the templater is not useful for anything other than HTML.
- String-based templater: A template library that implements templating logic, but that has no understanding of the content it is generating - it simply concatenates together strings, potenti
Picking the right architecture = Picking the right battles + Managing trade-offs
- Clarify and agree on the scope of the system
- User cases (description of sequences of events that, taken together, lead to a system doing something useful)
- Who is going to use it?
- How are they going to use it?