Don't create language_models.py twice

[cipher-training.git] / slides / caesar-break.html

diff --git a/slides/caesar-break.html b/slides/caesar-break.html
index 4d2ebfa0d01d556dbdd37599f3e4320f92fc4031..879244624f8a5e210c3495ee12794a1ae321d479 100644 (file)
--- a/slides/caesar-break.html
+++ b/slides/caesar-break.html
@@ -128,11 +128,11 @@ Use this to predict the probability of each letter, and hence the probability of
 
 ---
 
-# An infinite number of monkeys
+.float-right[![right-aligned Typing monkey](typingmonkeylarge.jpg)]
 
-What is the probability that this string of letters is a sample of English?
+# Naive Bayes, or the bag of letters
 
-## Naive Bayes, or the bag of letters
+What is the probability that this string of letters is a sample of English?
 
 Ignore letter order, just treat each letter individually.
 
@@ -234,8 +234,13 @@ def unaccent(text):
 
 1. Read from `shakespeare.txt`, `sherlock-holmes.txt`, and `war-and-peace.txt`.
 2. Find the frequencies (`.update()`)
-3. Sort by count 
-4. Write counts to `count_1l.txt` (`'text{}\n'.format()`)
+3. Sort by count (read the docs...)
+4. Write counts to `count_1l.txt` 
+```python
+with open('count_1l.txt', 'w') as f:
+    for each letter...:
+        f.write('text\t{}\n'.format(count))
+```
 
 ---
 
@@ -257,6 +262,8 @@ def unaccent(text):
 
 # Breaking caesar ciphers
 
+New file: `cipherbreak.py`
+
 ## Remember the basic idea
 
 ```