14. Prepared
15. Poor Economics
16. Atomic Habits
17. The Money Formula
18. The Hour between Dog and Wolf
19. What got you here wont get you There
20. The Upanishads: Stories of the
21. When Genius Failed – reading
    • Reading for the second time
22. When the Wolves Bite
23. A Guide to the Good Life
24. The Great Influenza
25. The Great Crash of 1929
26. Good Economics for Hard Times
27. Cribsheet
28. Confidence Game
29. Why We Sleep
30. Antifragile
31. Stress Test
32. That Will Never Work
33. Behind the Could
34. The Success Equation
35. Churchill’s Secret War
36. Big Mistakes
37. Concentrated Investing
38. Rebel Sultans: The Deccan from Khilji to Shivaji
39. The Courtesan, The Mahatma and the Italian Brahmin
40. Cambridge History of India: The Marathas

1. Berkshire Hathaway letters to shareholders 1965 – 2018
2. Buffet Partnership Letters 1957 – 1970
3. Marissa Mayer and the Fight to Save Yahoo
4. Thinking in Systems
5. Bottle of Lies
6. Dear Chairman
7. Who says Elephants Can’t Dance
8. The Misbehavior of Markets
9. Quality Investing
10. What I talk about when I talk about Running
11. Loonshots
12. The Investment Checklist
13. Uninhabitable Earth – didn’t finish

• conda cheatsheet

• Publish documentation created with sphinx to github. Note that you don’t need to install the extra package. You can bypass Jekyll by adding a .nojekyll file to the repo

• NumPy style documentation

• Miniconda: Quick Installing full scientific python on a new unix machine. Instructions for setting it up on Travis-CI

• python subprocess example in a unittest class

def setUp(self):
self.server_log_file = open('.tsdb_server.log.test','w')
self.server_proc = subprocess.Popen(['python', 'go_server.py']
,stdout=self.server_log_file,stderr=subprocess.STDOUT)
time.sleep(1)

def tearDown(self):
self.server_proc.terminate()
self.server_log_file.close()
time.sleep(1)

• Check if any python jobs are running in the background (of course this doesn’t have to be python)

jobs
ps aux | grep 'python'

• End-to-End Memory Networks for Question Answering in Python with very nice visualizations

• nngraph resources

• Oxford ML Practical

• Sample Code (harvardnlp) here and here and some more that I wrote. Important thing that I found was that there is little to no thought given to the initial values of model params and gradParams. Set them yourself.

• Convert .dot files (graphviz) between formats:

• PDF dot -Tpdf filename.dot -o filename.pdf

• PostScript dot -Tps filename.dot -o filename.ps

• bash shell conditionals

#!/bin/bash

if [ $1 == "-h" ]; then
echo "Syntax::sh scriptname output-file classifer-name num-epochs"
exit
fi

# check outputfile
if [ -z $1 ]; then
echo "Output file not specified. Using 'output.all' "
OUTFILE="output.all"
else
OUTFILE=$1
if [ -e $OUTFILE ]; then
echo "Emptying " $OUTFILE
rm $OUTFILE
fi
echo "Output File = " $OUTFILE
fi

• Get a specific file from a different branch on git

git checkout branch2 file.py

• Get a specific file from a different branch on git and check changes line by line

git checkout --patch branch2 file.py

Books:

• David Mackay -Machine Learning

• Data Intensive Application Design

Areas:

• Probabilistic Numerics

Papers / Blog Posts:

• NoSQL DBs

• The Unreasonable Effectiveness of Recurrent Neural Networks

Talks:

• Rob Pike – ‘Concurrency Is Not Parallelism’

Programming Languages:

• Javascript and React.js
• Haskell
• Julia

• agar – Food thickener

• roust – means exactly the same thing as rouse

• sabot – Dutch shoe

• eiger – dangerous Alpine peak

• inez – Don Juan’s Mother

• etui – small ornamental case for holding needles, thread etc

• orange pekoe – grade of black teas

• cosi fan tutte – Mozart Opera (translates to “Woman are like that”)

• orrery – model of the solar system, used to be made out of wood
• cur – rabid dog
• sca – genre of music that reggae came out of
• statal – of or relating to a state (usually a nation state)
• egad – expressing surprise (like oh god)
• roos – slang for kangaroos
• gnu – deer like animal found in Africa
• tse-tse – bees that spread disease
• petit four – small french pastries

Against Subtlety

Birthright

Does the Democratic Party have a Future

vim Cheatsheet

RStudio Cheatsheets

Useful Unix Tutorials

Time Series Modelling in R

Eric Zivot’s State Space Models Slides

awk

Found this helpful for going though log files since they are naturally separated into fields. Good general tutorial here.

Useful predefined variables. Good write up here

1. FILENAME – name of the file you’re in
2. NR – line number that you’re on (global)
3. FNR -line number that you’re on relative to current file
4. NF – number of “fields” or words separated by the given delimiter on the line.
5. FS – field seperator (space is the default)
6. OFS – ouput field seperator (space is the default)

Useful Code Snippets

select lines where the third column is equal to 2 and compute the mean sum of squares of the eighth, ninth and tenth columms
awk 'BEGIN {r=0; num=0} {if ($3==2) {r += $8^2 + $9^2 + $10^2; num++}} END {print r/num}' filename

select lines with a 0 and atleast 20 columns and print the first and last column
awk '/0/ {if (NF > 20) print $1,$NF}' log.spparks.4 > hyd_diff_temp_2

select lines from a file where the second column is larger than 20 and print the filename with some additional columns
awk ' {if($2 > 20) print FILENAME,$1*10,$2}' size_time_*_1

sed

Generally used to replace texts but can be used more powerfully. Useful tutorial here.
replace “size_time” with blank
sed 's/size_time_//'

replace “size_time_someNumber_1” with “someNumber”
sed 's/size_time_\([0-9]*\)_1/\1/'

Since Grantland got shut down

The B.S Report is now the B. S. Podcast

Hollywood Prospectus is now The Watch

NBA After Dark is now Sources Say

Slate

Culture Gabfest – Started listening to it during the two weeks in which we had no HP pods. Slightly higher brow with a slightly douchy who will occasionally rant about “fruit forward” wine.

Political Gabfest – American Politics was definitely a hole in my podcast world and this fills it nicely.

Other

Common Sense – Dan Carlin’s show on current events.

The Allusionist – Like a much shorter hardcore history about words. I like the short etymology section at the top of the show more than the actual show. Why is a warewolf called a warewolf and not a manwolf?