91–99 of 99 posts
1. Dvorak 2. Emacs 3. Clojure 4. Testing from a keyboard
Unless you are dead-set on dvorak, look into colemak. It is much easier to learn vs dvorak and keeps many common keys. Mac OS X and modern linux distros have it built in as well.
2) Blogging: I learn too much stuff to not pass on that knowledge.
3) DreamLeaves: I've had this "group" of mine on hiatus for too long. I need to build a functional platform to showcase all of our works and make all of us "rockstars" in our respective fields.
4) Marketing: "You dev guys, you got gold in your hands!" always say a friend of mine (let's say he's a "bank-guy"). Bad news though is, I could make the next facebook/instagram/w/ever, I wouldn't know how to distribute/advertise/sell it properly.
5) More time outside of code. Today, my life is split between coding for a job and coding for a passion but even those two are still centered around the same project.
But all this would be naught without... n+1) Follow a schedule.
1. sed and awk; 2. To use vim competently; 3. To touch-type; 4. Perl; 5. Polish; 6. To stay offline on Xmas day.
Out of curiosity, why Perl?
sed, awk and Perl practically don't have any competitors in their stride.
When you learn those tools, you basically realize that all the while you were using a hammer, while what you should been using is a screw driver.
1. Probability Bayesian statistics and its applications. A lot of things I want to understand like Probabilistic Graphical Models, Cryptography, and Computer Vision seem to be based in fundamental bayesian statistics I never really grokked that well. 2. EE and Computer architecture. I never studied any EE. The more I program, the more tempted I am to get closer to the metal. It's a little weird that I tell computers…
I'm also interested in "3. Visualization". Can you share how are you going to approach it? I'm interested in knowing what topics to cover, which books to consult, which tools to use.
* https://graphics.stanford.edu/wikis/cs448b-12-fall/
* http://ocw.mit.edu/resources/res-6-009-how-to-process-analyz...
Earlier quoted context omitted.
Out of curiosity, why Perl?
Plenty of reasons to. sed, awk and Perl practically don't have any competitors in their stride. When you learn those tools, you basically realize that all the while you were using a hammer, while what you should been using is a screw driver.
Machine learning.
Open source contribution workflow.
Advanced Algorithms from various websites.
1. Probability Bayesian statistics and its applications. A lot of things I want to understand like Probabilistic Graphical Models, Cryptography, and Computer Vision seem to be based in fundamental bayesian statistics I never really grokked that well. 2. EE and Computer architecture. I never studied any EE. The more I program, the more tempted I am to get closer to the metal. It's a little weird that I tell computers…
I'm also interested in "3. Visualization". Can you share how are you going to approach it? I'm interested in knowing what topics to cover, which books to consult, which tools to use.
I was planning to read Interactive Data Visualization for the Web http://ofps.oreilly.com/titles/9781449339739/index.html I think that's mostly an introduction to the tool (D3) but maybe has some info on visualization itself.
Also, this tutorial was an easy intro to D3: http://code.hazzens.com/d3tut/ Hopefully, the author continues to add to it.
Mike Bostock (author of D3) has some interesting blogs at: http://bost.ocks.org and also some great visualizations at http://bl.ocks.org/mbostock
A PHD in my office recommended The Grammar Of Graphics http://www.amazon.com/The-Grammar-Graphics-Statistics-Comput... It seems much more technical and statistical but could be an interesting set of ideas to synthesize. I'm planning on borrowing his copy.
Mike Bostock's stuff also led me to this page on Hive Plots which is a pretty cool description of how to do network visualization better: http://www.hiveplot.com
And I like Flowing Data as a blog: http://flowingdata.com/
This is all of course prior to actually having studied it. I'm hoping using these resources and playing with some toy projects will lead me down further paths. (Assuming I have time which I, of course, probably won't.)