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Matthew Bernhardt matt-bernhardt

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@-moz-document url-prefix("https://mit.primo.exlibrisgroup.com/discovery/search?vid=01MIT_INST:MIT&lang=en") {
/* Insert code here... */
body {
font-size: 16px;
}
div.header {
border-top: 2rem solid white;
}
.__xl div.header {
border-top-color: red;
@matt-bernhardt
matt-bernhardt / big-decision.md
Last active September 21, 2023 17:23
Mermaid and accessibility

This is a demonstration Mermaid diagram which implements a description tag. Does the VoiceOver screenreader find it?

graph LR;
      accTitle: Big Decisions;
      accDescr: This is the description for this Mermaid diagram. The diagram depicts the Bob's Burgers process for making big decisions;
      A[Identify Big Descision] --> B{Make Big Decision};
      B --> D[Be done];

If you are hearing this text, then you have left the diagram, and should have already heard the description contents.

@matt-bernhardt
matt-bernhardt / 1_theory_of_search.md
Created September 6, 2023 15:03
Mermaid diagrams describing some search architectures
---
title: Theory of search
---
flowchart
  direction LR
  Capture --> Interpret
  Interpret --> Match
  Match --> Rank
 Rank --> Present
@matt-bernhardt
matt-bernhardt / model170501.py
Created October 15, 2017 02:38
A simple python script that runs a monte carlo simulation of the remaining games in a Major League Soccer season. This is pretty coupled to the database I use, and some shim objects I wrote for that database - but the approach should be clear though.
import copy
import database
from log import Log
from output import Output
import numpy as np
def calculatePPG(data):
# This expects data in a form of
# {'MIN': {'Points': 8.0, 'PPG': 0.8888888888888888, 'GP': 9.0}, 'TOR': {'Points': 16.0, 'PPG': 1.7777777777777777, 'GP': 9.0}}
@matt-bernhardt
matt-bernhardt / yellow-machine-46ccee.lua
Created December 28, 2022 15:26
A patched version of the Yellowscribe LUA script
-- Bundled by luabundle {"rootModuleName":"Yellow Machine.46ccee.lua","version":"1.6.0"}
local __bundle_require, __bundle_loaded, __bundle_register, __bundle_modules = (function(superRequire)
local loadingPlaceholder = {[{}] = true}
local register
local modules = {}
local require
local loaded = {}
@matt-bernhardt
matt-bernhardt / README.md
Last active October 30, 2021 21:15 — forked from mbostock/.block
Interdisciplinarity at MIT

Mucking around with interdisciplinarity around MIT

.wpcf7 fieldset{margin-top:1.5rem;margin-bottom:1.5rem;border:1px solid #ccc;padding:1rem 1.5rem;width:75%}.wpcf7 .wpcf7-text,.wpcf7 .wpcf7-email,.wpcf7 .wpcf7-textarea{background-color:#fff;color:#000;font-size:14px}.wpcf7 .wpcf7-submit{-webkit-appearance:none;transition:background-color 0.25s, border 0.25s;border:1px solid #338bc5;border-radius:3px;padding:5px 10px;background-color:#338bc5;background-image:none;font-size:1rem;color:#fff;margin-top:10px}.wpcf7 legend{padding:0 1rem;font-size:0.9rem;color:#595959;text-transform:uppercase;width:auto}.wpcf7 .button-primary.green,.wpcf7 .wrap-outer-header-local .green.action-auth{border:1px solid #3b815d;background-color:#43926a;margin:0;max-width:15rem}.wpcf7 .button-primary.green:focus,.wpcf7 .wrap-outer-header-local .green.action-auth:focus,.wpcf7 .button-primary.green:hover,.wpcf7 .wrap-outer-header-local .green.action-auth:hover{background-color:#2ea76a;border-color:#43926a}.wpcf7 .wpcf7-list-item{display:block}.loading-container{display:block;width:100%;he
@matt-bernhardt
matt-bernhardt / year-over-year-ppg.csv
Created February 29, 2020 21:43
A dataset of MLS team performance (measured by Points Per Game) from year to year between 1996 and 2019. Brief context at https://twitter.com/bernhardtsoccer/status/1233859569983639552
ID Team Year1 Pts1 GP1 PPG1 Playoffs1 Playoffs1Int Year2 Pts2 GP2 PPG2 Playoffs2 Playoffs2Int
1 Colorado Rapids 1996 29 32 0.9063 Did Not Qualify 0 1997 38 32 1.1875 Finalist 4
2 Columbus Crew 1996 37 32 1.1563 Quarterfinalist 2 1997 39 32 1.2188 Semifinalist 3
3 D.C. United 1996 46 32 1.4375 Champion 5 1997 55 32 1.7188 Champion 5
4 FC Dallas 1996 41 32 1.2813 Quarterfinalist 2 1997 42 32 1.3125 Semifinalist 3
5 Los Angeles Galaxy 1996 49 32 1.5313 Finalist 4 1997 44 32 1.375 Quarterfinalist 2
6 New England Revolution 1996 33 32 1.0313 Did Not Qualify 0 1997 37 32 1.1563 Quarterfinalist 2
7 New York Red Bulls 1996 39 32 1.2188 Quarterfinalist 2 1997 35 32 1.0938 Did Not Qualify 0
8 San Jose Earthquakes 1996 39 32 1.2188 Quarterfinalist 2 1997 30 32 0.9375 Did Not Qualify 0
9 Sporting Kansas City 1996 41 32 1.2813 Semifinalist 3 1997 49 32 1.5313 Quarterfinalist 2
@matt-bernhardt
matt-bernhardt / 4lda-notes-only.py
Last active December 18, 2019 17:17
2019 Learning Days - attempting a rudimentary Recommender System with ASpace data
from __future__ import absolute_import
import csv
from time import time
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction import text
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.decomposition import LatentDirichletAllocation
# This attempts to perform LDA on the text of the notes from ArchivesSpace.