| .repitem { | |
| display: flex; | |
| align-items: center; | |
| margin-bottom: 3px; | |
| justify-content: space-between; | |
| } | |
| .sheet-ability-value, .sheet-ability-button { | |
| display: inline-block !important; | |
| } | |
| .sheet-flex-between { |
The purpose of this document is to make recommendations on how to browse in a privacy and security conscious manner. This information is compiled from a number of sources, which are referenced throughout the document, as well as my own experiences with the described technologies.
I welcome contributions and comments on the information contained. Please see the How to Contribute section for information on contributing your own knowledge.
If you were to give recommendations to your "little brother/sister" on things that they need to do to become a data scientist, what would those things be?
I think the "Data Science Venn Diagram" (http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram) is a great place to start. You need three things to be a good data scientist:
| // Use Gists to store code you would like to remember later on | |
| console.log(window); // log the "window" object to the console |
| ai. 14170 IN MX 10 mail.offshore.ai. ;; Anguilla | |
| as. 21371 IN MX 10 cmh.relay.gdns.net. ;; American Samoa | |
| as. 21371 IN MX 10 dca.relay.gdns.net. ;; American Samoa | |
| bj. 86176 IN MX 20 mail6.domain-mail.com. ;; Benin | |
| cf. 3379 IN MX 10 mail.intnet.cf. ;; Central African Republic | |
| dj. 345488 IN MX 5 relais2.intnet.dj. ;; Djibouti |
| #! /usr/bin/perl | |
| # | |
| # Script written to pull IP data from openIOC and search Splunk. | |
| # | |
| use strict; | |
| use warnings; | |
| $|=1; |
| # Oona Räisänen 2013 | |
| @emoji = qw( 🌀 🌂 🌅 🌈 🌙 🌞 🌟 🌠 🌰 🌱 🌲 🌳 🌴 🌵 🌷 🌸 | |
| 🌹 🌺 🌻 🌼 🌽 🌾 🌿 🍀 🍁 🍂 🍃 🍄 🍅 🍆 🍇 🍈 | |
| 🍉 🍊 🍋 🍌 🍍 🍎 🍏 🍐 🍑 🍒 🍓 🍔 🍕 🍖 🍗 🍘 | |
| 🍜 🍝 🍞 🍟 🍠 🍡 🍢 🍣 🍤 🍥 🍦 🍧 🍨 🍩 🍪 🍫 | |
| 🍬 🍭 🍮 🍯 🍰 🍱 🍲 🍳 🍴 🍵 🍶 🍷 🍸 🍹 🍺 🍻 | |
| 🍼 🎀 🎁 🎂 🎃 🎄 🎅 🎈 🎉 🎊 🎋 🎌 🎍 🎎 🎏 🎒 | |
| 🎓 🎠 🎡 🎢 🎣 🎤 🎥 🎦 🎧 🎨 🎩 🎪 🎫 🎬 🎭 🎮 | |
| 🎯 🎰 🎱 🎲 🎳 🎴 🎵 🎷 🎸 🎹 🎺 🎻 🎽 🎾 🎿 🏀 |
[Various details redacted.]
I'm currently about to start a Geography degree at the University of [Redacted] at [Redacted] with a focus in GIS, and I've been finding that I have an interest in working with imagery. Obviously I should take Remote Sensing and other similar classes, but I'm the type of person who likes to self learn as well. So my question is this: What recommendations would you give to a student who is interested in working with imagery? Are there any self study paths that you could recommend?
I’m self-taught myself, and there are a lot of important topics in GIS that I don’t know anything about, so I can’t give comprehensive advice. I haven’t arrived anywhere; I’m just ten minutes ahead in the convoy we’re both in. Take these recommendations critically.
Find interesting people. You’ll learn a lot more from a great professor (or mentor, or friend, or tutorial) talking about something outside your specialty than you will from someone boring who’s working on exactly what you’re interested in.
| // Just before switching jobs: | |
| // Add one of these. | |
| // Preferably into the same commit where you do a large merge. | |
| // | |
| // This started as a tweet with a joke of "C++ pro-tip: #define private public", | |
| // and then it quickly escalated into more and more evil suggestions. | |
| // I've tried to capture interesting suggestions here. | |
| // | |
| // Contributors: @r2d2rigo, @joeldevahl, @msinilo, @_Humus_, | |
| // @YuriyODonnell, @rygorous, @cmuratori, @mike_acton, @grumpygiant, |