- Project Rhea — online learning community where students teach other students. The tutorials here vary in detail and quality. Generally they are more that a definition at mathworld, less than a step by step. Good for getting the highlights on an unfamiliar topic
- Wolfram Mathworld — Like wikipedia, but only for Math. Go here when you have no idea what an "Isotopic Kernel is or why you would care. Mathworld will give you 80+ entries that are linked.
- Wikipedia Math Portal — the place to find everything math related on Wikipedia.
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Getting Started with R. | |
I'll update this as I keep adding information. | |
Just to play around with R. There's a great PDF built into the environment | |
Download R: http://www.r-project.org/ Install the R Package | |
Once you fire up the R Shell (installed in /Applications by default) |
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.../inception (127)%make | |
gcc -g -Wall -m32 -c -o inception.o inception.c | |
gcc -g -Wall -m32 -g -o inception inception.o -lpthread | |
~/tmp/inception %./inception | |
Dreamer [Fischer], level [1], priority [19], policy [OTHER] | |
Dreamer [Cobb], level [1], priority [19], policy [OTHER] | |
Dreamer [Ariadne], level [1], priority [19], policy [OTHER] | |
Dreamer [Arthur], level [1], priority [19], policy [OTHER] | |
Dreamer [Eames], level [1], priority [19], policy [OTHER] | |
Dreamer [Yusuf], level [1], priority [19], policy [OTHER] |
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- Whisky notes: http://www.whisky-pages.com/ | |
*** http://weka.wikispaces.com/Use+Weka+in+your+Java+code | |
- http://cran.r-project.org/web/views/Bayesian.html - a metric shit tonne of packages for R | |
- http://www.celiagreen.com/charlesmccreery/statistics/bayestutorial.pdf - Greate illustrated guide to bayesian trees | |
- http://www.cs.waikato.ac.nz/~remco/weka_bn/bayesnet.html | |
- http://en.wikipedia.org/wiki/Chain_rule_(probability) - Chain Rule of probablity | |
- http://aima.cs.berkeley.edu/ - AI a Modern Approach (full HTML online) | |
- http://www.labmedinfo.org/sites/default/files/file/publications/lmi339.pdf - Hierarchical Bayes Clasifiers for Uncertain Data | |
- http://people.csail.mit.edu/jrennie/papers/icml03-nb.pdf - Naieve Bayes Text Classifiers | |
- https://www.cra.com/pdf/bnetbuilderbackground.pdf - |
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Most Duty free bottles are 1L in size - plan accordingly :) | |
Further more there are a few that are only sold in Duty Free: | |
Highland Park 16 Year (Airport Only) | |
Laphroaig Tripple Wood 1L (Mostly Airport in 1L) | |
Johnny Walker Double Black (Airport only) | |
Ardbeg's that are hard to find in the US |
How do we deal with complex structures when we want to assign items at different levels inside the structure? (Lets skip if this muddies the intent of the code or not and just deal with how it can be done ;) )
# Build up a map
m = %{ r: %{foo: "foo", bar: "bar", baz: %{qux: "qiz wiz"}}}
I hereby claim:
- I am daksis on github.
- I am daksis (https://keybase.io/daksis) on keybase.
- I have a public key whose fingerprint is 5AB1 38C2 C149 1B86 29D8 A67C 3982 2152 8424 86D0
To claim this, I am signing this object:
This is a braindump of my progress over the weekend to look into Bluetooth support on Nerves. While Bluetooth has a lot of specs, supporting a subset of BLE that makes it easy for Nerves devices to communicate with cell phones and back would be generally useful.
There are two options for BLE support on Nerves:
- Make a custom Nerves system that uses
bluez
- Use
Harald
bluez
is a fairly complete stack that doesn't integrate well with Nerves and is hard to debug when things go wrong.