abehmiel

These notes may have errors and omissions. I couldn’t get the names of a lot of the speakers and there are some places where I was thinking or distracted. I make no claims as to the completeness of this information

Algorithmic transparency legislation hearing 10/16/17

James Vaca, Chair of NYCC committee on technology

16-96 2017 Measures of transparency when NYC uses algorithms to impose penalties, police persons

• Requires publication of source code and querying systems with sample data

• If left unchecked, algorithms can have negative repercussions
• Algorithms are a way of encoding assumptions

abehmiel

class Graph:
  def __init__(self):
    self.nodes = set()
    self.edges = defaultdict(list)
    self.distances = {}

  def add_node(self, value):
    self.nodes.add(value)

  def add_edge(self, from_node, to_node, distance):

abehmiel

Taken at Babycastles in NYC 10/11 NYC Botmakers Meetup for more info: https://www.meetup.com/botmakers/ I make no claims as to the completeness of these notes

Conversational chatbots - Gautam

3 days of full development (idk what a bot is to v0.1)

chatbot client -> chatbot server -> conversation API

What is the weather in nyc? turn that into intent which the server can understand

abehmiel

import difflib

# input data
df1 = DataFrame([[1],[2],[3],[4],[5]], index=['one','two','three','four','five'], columns=['number'])
df2 = DataFrame([['a'],['b'],['c'],['d'],['e']], index=['one','too','three','fours','five'], columns=['letter'])

# want to obtain:
#        number letter
# one         1      a
# two         2      b

abehmiel

def create_figure(size=3.6,nxticks=6):
    import matplotlib
    from matplotlib.ticker import MaxNLocator
    figure=matplotlib.pyplot.figure(figsize=(size,size)) 
    ax = figure.add_subplot(1, 1, 1, position = [0.2, 0.15, 0.75, 0.75]) 
    ax.xaxis.set_major_locator(MaxNLocator(nxticks)) 
    return ax

def format_axes(ax,xf='%d',yf='%d',nxticks=6,nyticks=6,labelsize=10):
    import pylab

abehmiel

# It's really stupid when the gov't releases pdf's of tabular data. So I made a quick, hacky script to
# fix their mistakes for them. (I'm referring to https://t.co/oOyhHNVvjS )

# requirements:
# pandas
# tabula-py

import pandas as pd
from tabula import read_pdf

abehmiel

abehmiel

abehmiel

RegEx Cheatsheet

Contents:

1. Special characters
2. Quantifiers
3. Special sequences
4. Useful examples

abehmiel

qpdf --password=passwd --decrypt orig.pdf decrypted.pdf

#To input the password
read -s -p "Password: " password && qpdf --password=$password --decrypt orig.pdf decrypted.pdf