content update

1 files changed, 46 insertions, 1 deletions

diff --git a/slides/presentations/basic-math-in-programming/default.pug b/slides/presentations/basic-math-in-programming/default.pug
index af5ee90..92b1474 100644
--- a/slides/presentations/basic-math-in-programming/default.pug
+++ b/slides/presentations/basic-math-in-programming/default.pug
@@ -16,12 +16,57 @@ section
 
   ul
     li We search for code example instead of algorithms.
-    li We copy and paste and do testing on trial&error principle.
+    li We copy and paste and do testing on trial&error principle.
     li We don't take enough time to properly understand problem we a re trying to solve.
     li Brute force solutions we make are usually not optimized
 
 
 section
+  h2 Levenshtein distance
+  p The Levenshtein distance is a string metric for measuring difference between two sequences. Informally, the Levenshtein distance between two words is the minimum number of single-character edits (i.e. insertions, deletions or substitutions) required to change one word into the other.
+
+  hr
+
+  div.center
+    img(src="levenshtein-distance.svg")
+
+  hr
+
+  pre
+    code.language-python
+      | def levenshtein(seq1, seq2):
+      |   oneago = None
+      |   thisrow = range(1, len(seq2) + 1) + [0]
+      |   for x in xrange(len(seq1)):
+      |     twoago, oneago, thisrow = oneago, thisrow, [0] * len(seq2) + [x + 1]
+      |     for y in xrange(len(seq2)):
+      |       delcost = oneago[y] + 1
+      |       addcost = thisrow[y - 1] + 1
+      |       subcost = oneago[y - 1] + (seq1[x] != seq2[y])
+      |       thisrow[y] = min(delcost, addcost, subcost)
+      |   return thisrow[len(seq2) - 1]
+
+
+  hr
+
+  h4 Going further
+  ol
+    li https://en.wikibooks.org/wiki/Algorithm_Implementation/Strings/Levenshtein_distance
+    li https://en.wikipedia.org/wiki/Levenshtein_distance
+    li https://rosettacode.org/wiki/Levenshtein_distance
+
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+section
   h2 Basic linear algebra
 
   pre