DavidMertz

Configure your system to look like following to make sure that Notebooks will always be pushed to GitHub without their output. This will make for smaller saved files, but more relevantly, also ones that are easier to diff (and that git will merge more cleanly).

% cat ~/.gitattributes
*.ipynb    filter=dropoutput_ipynb

% cat ~/bin/ipynb_output_filter.py
#!/usr/bin/env python
import sys
version = None

DavidMertz

David is founder of KDM Training, a partnership dedicated to educating developers and data
scientists in machine learning and scientific computing. He created the data science training
program for Anaconda Inc. and was a senior trainer for them. With the advent of deep neural
networks he has turned to training our robot overlords as well.

He was honored to work for 8 years with D. E. Shaw Research, who have built the world's fastest,
highly-specialized (down to the ASICs and network layer), supercomputer for performing molecular
dynamics.

David was a Director of the PSF for six years, and remains co-chair of its Trademarks

DavidMertz

absolutise
absolutised
absolutises
absolutive
absolutize
absolutized
absolutizes
abstemious
abstemiously
abstentious

DavidMertz

# A bit of cleverness to create a new sequence for infinite iterators
from collections.abc import Sequence

class MonotonicExpandingSequence(Sequence):
    def __init__(self, iterator):
        self.iterator = iterator
        self._cache = []
        
    def __getitem__(self, index):
        while len(self._cache) <= index:

DavidMertz

#!/usr/bin/env julia

####################################################
### Released to the Public Domain by David Mertz ###
####################################################

#= Usage examples:
$ cat schedule
| Course title                      | Time (EST) | Date     |
|-----------------------------------|------------|----------|

DavidMertz

% head -30 suffix-frequency-en.txt
('es', 34752)
('ed', 20197)
('ng', 18910)
('ing', 18619)
('er', 10745)
('rs', 10744)
('ns', 8716)
('ts', 8534)
('ly', 8492)

DavidMertz

(base) 530-tmp % python thread_kill.py
[1, 2, 3, 4, 5, 1]
[1, 2, 3, 4, 5, 1, 2]
[1, 2, 3, 4, 5, 1, 2, 3]
[1, 2, 3, 4, 5, 1, 2, 3, 4]
[1, 2, 3, 4, 5, 1, 2, 3, 4, 5]
[1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1]
[1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2]
[1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3]
[1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4]

DavidMertz

-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA512

January 8, 2022

I, David Quintyn Mertz, residing at 45 Main Street, Dexter Maine 04930, 
declare this to be my Will, and I revoke any and all wills and codicils 
I previously made.

    Proof of not-earlier-date: New York Times headline for today's date:

DavidMertz

-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA512

DURABLE POWER OF ATTORNEY FOR HEALTH CARE

I, David Quintyn Mertz, of 45 Main Street, Dexter ME 04930 USA, being of sound
mind, voluntarily create this Durable Power of Attorney for Health Care.


PRIOR DESIGNATIONS

DavidMertz

Cleaning Data for Effective Data Science
Doing the other 80% of the work

    In order for something to become clean, something else must become dirty.
    –Imbesi's Law of the Conservation of Filth

It is something of a truism in data science, data analysis, or machine learning 
that most of the work needed to do your actual work lies in cleaning your data. 
The subtitle of this work alludes to a commonly assigned percentage. A keynote 
speaker I listened to at a data science conference a few years ago made a joke—