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@egonSchiele
egonSchiele / phan_conditional.diff
Created Mar 11, 2016
Add a closure for conditionals to phan
View phan_conditional.diff
diff --git a/src/Phan/Analysis/PreOrderAnalysisVisitor.php b/src/Phan/Analysis/PreOrderAnalysisVisitor.php
index 8650cd3..feaaee4 100644
--- a/src/Phan/Analysis/PreOrderAnalysisVisitor.php
+++ b/src/Phan/Analysis/PreOrderAnalysisVisitor.php
@@ -508,11 +508,16 @@ class PreOrderAnalysisVisitor extends ScopeVisitor
*/
public function visitIfElem(Node $node) : Context
{
+ $closure_fqsen =
+ FullyQualifiedFunctionName::fromClosureInContext(
@egonSchiele
egonSchiele / non_linear_classification.m
Created Mar 10, 2016
Non-linear classification example
View non_linear_classification.m
% my training data.
% so if x > 3 || x < 7, y = 1, otherwise y = 0.
x = 1:100;
y = [0, 0, 0, 1, 1, 1, 1, zeros(1, 93)];
% instead of theta' * x, I'm trying to create
% a non-linear decision boundary.
% So instead of y = theta_0 + theta_1 * x, I use:
function result = h(x, theta)
result = sigmoid(theta(1) + theta(2) * x + theta(3) * ((x - theta(4))^2));
@egonSchiele
egonSchiele / logistic_regression_grapefruit.m
Created Mar 10, 2016
Logistic regression for orange vs grapefruit
View logistic_regression_grapefruit.m
% data
x = [1, 2, 3, 4, 5, 6];
y = [0, 0, 0, 1, 1, 1];
% function to calculate the predicted value
function result = h(x, t0, t1)
result = sigmoid(t0 + t1 * x);
end
% sigmoid function
View linear_regression_with_fminunc.m
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);
View logistic_regression.m
% 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
egonSchiele / regression.m
Last active Aug 31, 2018
Linear regression in Octave
View regression.m
% 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
egonSchiele / Main.hs
Last active Nov 12, 2015
kcombinations
View Main.hs
{-# 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 ()
View keybase.md

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
egonSchiele / why.markdown
Last active Jul 20, 2018
Why read Grokking Algorithms?
View why.markdown

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.

View notes_on_cameras.markdown

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.

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