annikakouhia

# Need Finding Interviews


## Interview 1:
* name: Annika Kouhia / Morgan Sorbaro 
* date: 09/23/2019
* occupation: Dartmouth Professor
* location: Fairchild
* interview partner: Professor Sneddon

annikakouhia

# Need Finding Interviews


## Interview 1:
* name: Annika Kouhia
* date: 09/20/2019  
* occupation: Professor
* location: Sudikoff
* interview partner: Tim Pierson

annikakouhia

# Need Finding Interviews


## Interview 1:
* name: Annika Kouhia
* date: 09/19/2019
* occupation: Student
* location: Dartmouth College
* interview partner: Madison Hazard

annikakouhia

/*This was a lab I completed with my friend Morgan for our CS10 course this past quarter at Dartmouth
 * Brown University mapped out a huge document made up of tons of sentences from books, magazines, newspapers, etc.
 * and then made a second document where each entry was the part of speech for the corresponding entry in the first
 * document.
 * For this lab, we were given the first and second document from Brown, and then used the Viterbi algorithm to basically
 * "teach" our program how to take in another document (we were given test documents with solutions for class) or user input.
 * and output the corresponding part of speech.
 * To deduce what each word (from the user input or from a document you put in) was in terms of parts of speech, the computer
 * relied on two things. First, was the probability that the word was as certain POS based on what POS the word before it was,
 * and second was the probability that the word was a certain POS based on what the word actually was (like the probability that

annikakouhia

# Annika Kouhia
# CS76 Artificial Intelligence
# October 2017
# SAT2 class holds the implementation of walkSat and gSat
# along with a lot of useful helper methods to store and access data efficiently

from random import *
from timeit import default_timer as timer

class SAT2: