egonSchiele

x = [1000, 2000, 4000];
y = [200000, 250000, 300000];

% given a theta_0 and theta_1, this function calculates
% their cost. We don't need this function, strictly speaking...
% but it is nice to print out the costs as gradient descent iterates.
% We should see the cost go down every time the values of theta get updated.
function distance = cost(theta)
  theta_0 = theta(1);
  theta_1 = theta(2);

egonSchiele

% my training data.
% so if x > 3 || x < 7, y = 1, otherwise y = 0.
x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
y = [0, 0, 0, 1, 1, 1, 0, 0, 0, 0];

% instead of theta' * x, I'm trying to create
% a non-linear decision boundary.
function result = h(x, theta)
  result = sigmoid(theta(1) + theta(2) * x + theta(3) * ((x - theta(4))^2));
end

egonSchiele

% scaled features.
% x = square feet
% y = sale price
x = [1, 2, 4];
y = [2, 2.5,  3];

% function to calculate the predicted value
function result = h(x, t0, t1)
  result = t0 + t1 * x;
end

egonSchiele

{-# LANGUAGE MultiWayIf #-}
import Data.List
import Control.Monad
import Control.Monad.Trans.Writer

kcombinations n arr = snd . runWriter $ combos [] 1 n arr

combos :: (Eq a) => [a] -> Int -> Int -> [a] -> Writer [[a]] ()
combos acc step n array = forM_ (zip array [1..]) $ \(val, i) -> if
  | val `elem` acc -> return ()

egonSchiele

Keybase proof

I hereby claim:

• I am egonschiele on github.
• I am adit (https://keybase.io/adit) on keybase.
• I have a public key whose fingerprint is 31AE C08A 8B28 F75B 596D 8146 0264 FC99 3D75 484F

To claim this, I am signing this object:

egonSchiele

If you have already taken a course in algorithms, why read Grokking Algorithms (manning.com/bhargava)?

If you were learning graph algorithms, which approach would you prefer:

1. Imagine you have to take public transit from your home to your office. How do you figure out the fastest route? Use graph algorithms! OR

2. We can choose between two standard ways to represent a graph G = (V, E): as a collection of adjacency lists or as an adjacency matrix. Either way applies to both directed and undirected graphs.

I prefer the first way: lead with lots of examples, and clear writing. The second way is an excerpt from "Introduction to Algorithms"...that's how they start their section on graph algorithms.

egonSchiele

Notes on cameras

Lenses

Focal length

Prime (fixed) lens

If it says 17mm, it's fixed at that...you can't zoom in or out. Advantages: cheaper.

egonSchiele

#!/usr/bin/env ruby
require 'tempfile'

def make_row cols, style=""
  "<tr style='#{style}'><td>" + cols.join("</td><td>") + "</td></tr>"
end

if ARGV.empty?
  puts %{
Usage: #{$0} [file] where file has col list for a hive table, then a blank line, then some sample rows

egonSchiele

def generate_valid_isbn
  prefix = 978.to_s # must be 978 or 979
  registration_group_element = rand(10).to_s
  registrant_element = (rand(90000) + 10000).to_s
  publication_element = (rand(900) + 100).to_s
  _isbn = prefix + registration_group_element + registrant_element + publication_element
  check_digit = 0
  i = 0
  _isbn.each_char do |letter|
    i+= 1

egonSchiele

 trap("SIGINT") do
   puts "goodbye!"
   # exit
 end

 while true
 end