,Unnamed: 0,Chapter,Midterm,Model,Condition,Question,Answer,questionId
0,1848,slp_chapter9_3,midterm_2,GPT3,Fewshot,"What do you need in order to train a classifier?
","In order to train a classifier, you need to treat the target word and a neighboring context word as positive examples.",1848
1,2424,chapter19_3,midterm_2,T5,GoodSummary,What can be used to find the smallest decision tree?,heuristics,2424
2,1415,slp_chapter6_4,midterm_2,GPT3,Zero,"What is the dot product of the two vectors 
",The dot product of the two vectors is,1415
3,2880,chapter16_1,midterm_2,T5,BadSummary,What do simple decisions assign probability to each possible current state s?,P(s),2880
4,4776,chapter13_3,midterm_2,T5,Best Condition - with Davinci,What can have exponential time and space complexity even when the number of parents per node is bounded?,Multiply connected networks,4776
5,4758,chapter13_1,midterm_2,T5,Best Condition - with Davinci,What does each node correspond to?,random variable,4758
6,6115,chapter_2_4_1,1st midterm,GPT3,From GPT-3 generated summary,"What is the key challenge for ai?
","The key challenge for ai is to find out how to write programs that, to the extent possible, produce rational behavior from a smallish program rather than from a vast table.",6115
7,465,chapter7_2,midterm_1,GPT3,GoodSummary,"What is an agent? 
",An agent is an entity that draws conclusions from available info and it's guaranteed to be right if the info is right.,465
8,4365,chapter2_1,midterm_1,T5,Best Condition - with Davinci,How many kinds of percepts does a vacuum cleaner agent have?,three,4365
9,6309,chapter_2_2_3,1st midterm,T5,From GPT-3 generated summary,The rational choice depends only on what?,percept sequence to date,6309
10,4173,slp_chapter4_5,midterm_2,T5,Fewshot,What is not a good metric when you want to discover something rare?,Accuracy,4173
11,1441,slp_chapter6_12,midterm_2,GPT3,Zero,"What are the two ways to account for the inherent variability of embedding algorithms?
",The two ways to account for the inherent variability of embedding algorithms are to train multiple embeddings and average the results.,1441
12,973,slp_chapter9_1,midterm_2,GPT3,BadSummary,"What are the advantages of neural language models over n-gram language models?
","Neural language models have several advantages over n-gram lms:
they don’t need smoothing
they can handle much longer histories.
they can generalize over contexts of similar words.
neural lms tend to have much higher predictive accuracy than n-gram lms.",973
13,4672,chapter12_2,midterm_2,T5,Best Condition - with Davinci,What is the probability of a proposition before taking into account any additional evidence?,prior probability,4672
14,5559,chapter_2_2_3,1st midterm,T5,From raw text,Doing actions to modify future percepts is sometimes called what?,information gathering,5559
15,3783,chapter2_4,midterm_1,T5,Fewshot,What does an agent program take to make a decision?,current percept sequence,3783
16,698,slp_chapter6_2,midterm_2,GPT3,GoodSummary,"What is the difference between vector semantics and the standard way to represent word meaning in nlp?
","The difference between vector semantics and the standard way to represent word meaning in nlp is that vector semantics is a way to represent word meaning in nlp by representing a word as a point in a multidimensional semantic space that is derived from the distributions of word neighbors.
summary
vectors semantics is the standard way to represent word meaning in nlp. the idea of vector semantics is to represent a word as a point in a multidimensional semantic space that is derived from the distributions of word neighbors. vectors for representing words are called embeddings.",698
17,4548,chapter7_2,midterm_1,T5,Best Condition - with Davinci,How are rooms connected in the Wumpus world?,passages,4548
18,776,chapter16_1,midterm_1,GPT3,BadSummary,"What is the expected utility?
",The expected utility is the average utility over all outcomes.,776
19,5369,chapter_27_1_1,1st midterm,T5,From raw text,What type of rules were popular in the 1980s but have been eclipsed by new approaches?,logical,5369
20,1003,slp_chapter6_11,midterm_2,GPT3,BadSummary,"What are some ways that bias in embeddings can be reduced?
",Bias in embeddings can be reduced by changing the training,1003
21,1117,chapter7_1,midterm_1,GPT3,Zero,"What is the initial knowledge base (kb) like?
",The initial knowledge base (kb) has background knowledge about the environment.,1117
22,4946,slp_chapter7_1,midterm_2,T5,Best Condition - with Davinci,What is a variant of the sigmoid that ranges from -1 to +1?,tanh function,4946
23,6042,chapter_27_1_1,1st midterm,GPT3,From GPT-3 generated summary,"What is the qualification problem?
",The qualification problem is the problem of capturing every contingency of appropriate behavior in a set of necessary and sufficient logical rules.,6042
24,6088,chapter_2_2_2,1st midterm,GPT3,From GPT-3 generated summary,"What is a rational agent expected to do?
","A rational agent is expected to select an action that is expected to maximize its performance measure, given the evidence provided by the percept sequence and whatever built-in knowledge the agent has.",6088
25,6068,chapter_2,1st midterm,GPT3,From GPT-3 generated summary,"What is an agent?
",An agent is a mechanism that interacts with its environment to achieve a goal.,6068
26,2645,slp_chapter7_7,midterm_2,T5,GoodSummary,What is cross-entropy?,negative log likelihood,2645
27,353,chapter1_1,midterm_1,GPT3,Best Condition - with Davinci,"What is the cognitive modeling approach?
","The cognitive modeling approach is an approach in which human thought is learned through introspection, psychological experiments, and brain imaging.",353
28,1575,chapter7_2,midterm_1,GPT3,Fewshot,"What are the sensors of the wumpus world?
","The sensors of the wumpus world are stench, breeze, glitter, bump, and scream.",1575
29,5602,chapter_2_3_2,1st midterm,T5,From raw text,Why is an environment partially observable?,noisy and inaccurate sensors,5602
30,1368,slp_chapter7_2,midterm_2,GPT3,Zero,"How many layers does a network of perceptrons need in order to solve the xor problem?
",A network of perceptrons needs at least two layers in order to solve the xor problem.,1368
31,6282,chapter_2_2,1st midterm,T5,From GPT-3 generated summary,What is the term for the notion that we evaluate an agent’s behavior by its consequences?,consequentialism,6282
32,6432,chapter_3_4_1,1st midterm,T5,From GPT-3 generated summary,What are both time and space complexity?,Exponential bounds,6432
33,360,chapter27_1,midterm_1,GPT3,GoodSummary,"Who thinks that machines are limited by the mathematical objection?
","Jr lucas thinks that machines are limited by the mathematical objection, so they are inferior to human.",360
34,5929,chapter_3_4_1,1st midterm,T5,From raw text,What is the evaluation function of BEST-FIRST-SEARCH?,the depth of the node,5929
35,822,chapter17_1,midterm_2,GPT3,BadSummary,"What is dynamic programming?
",Dynamic programming is a method for solving mdps that simplifies a problem by recursively breaking it into smaller pieces and remembering the optimal solutions to the pieces.,822
36,141,SLP_chapter3_3,midterm_2,GPT3,Best Condition - with Davinci,"How can we generate bigrams?
"," we can generate bigrams by generating random bigrams that start with s, then choosing random bigrams stating with the next word and so on until the sentence end token is hit.",141
37,2285,chapter12_1,midterm_2,T5,GoodSummary,What are the two main causes of uncertainty in humans?,laziness and ignorance,2285
38,5416,chapter_27_1_4,1st midterm,T5,From raw text,What did Turing think could pass the Turing test by the year 2000?,a computer with a storage of a billion units,5416
39,64,chapter16_2,midterm_2,GPT3,Best Condition - with Davinci,"What is monotonicity?
",Monotonicity is the constraint on rational preferences that requires that preferences be monotonic.,64
40,3981,chapter17_2,midterm_2,T5,Fewshot,Value iteration converges faster for what?,small values of gamma,3981
41,2098,chapter6_5,midterm_1,T5,GoodSummary,How can we reduce the search space?,symmetry-breaking constraints,2098
42,3216,chapter3_5,midterm_1,T5,Zero,What are suboptimal search algorithms?,"bounded, bounded-cost, or unbounded-cost",3216
43,3585,slp_chapter4_10,midterm_2,T5,Zero,What can be used to create representational harms?,stereotypes,3585
44,6235,chapter_27_1,1st midterm,T5,From GPT-3 generated summary,"Who wrote ""aerial flight is one of the great class of problems with which man can never cope""?",Simon Newcomb,6235
45,5226,chapter_3_4_5,1st midterm,GPT3,From raw text,"How does bidirectional search differ from unidirectional search?
","Unlike unidirectional search, bidirectional search simultaneously searches forward from the initial state and backwards from the goal state(s).",5226
46,4045,chapter12_4,midterm_2,T5,Fewshot,When does independence fail to hold?,whenever a connection (also very indirect) exists between two variables,4045
47,1000,slp_chapter6_11,midterm_2,GPT3,BadSummary,"What is gendered term harm?
",Gendered term harm is a harm caused by a system that becomes more gendered in embedding space than it was in the input text statistics.,1000
48,3495,chapter19_2,midterm_2,T5,Zero,What can we look for for each function close to y?,best fit function,3495
49,1252,chapter13_1,midterm_2,GPT3,Zero,"What is a node's associated probability information?
",A node's associated probability information is the quantification of the effect of the parent nodes on the node using a finite number of parameters.,1252
50,5088,chapter_27_1_4,1st midterm,GPT3,From raw text,"What is the purpose of the turing test?
",The purpose of the turing test is to measure a program’s ability to fool an interrogator into thinking the program is human.,5088
51,2827,chapter5_3,midterm_1,T5,BadSummary,What is the evaulation function for the min max value?,an herustic,2827
52,6121,chapter_2_4_4,1st midterm,GPT3,From GPT-3 generated summary,"What is goal information?
","Goal information is information that describes situations that are desirable, and the agent program can use this information to choose actions that will achieve the goal.",6121
53,4574,chapter7_5,midterm_1,T5,Best Condition - with Davinci,What is an automated reasoning technique that applies rules of inference directly to the sentences in our knowledge base?,Inference rules,4574
54,1904,chapter27_1,midterm_1,T5,GoodSummary,What is the simplest logical agent that cannot capture every rule?,GOFAI,1904
55,3002,slp_chapter4_2,midterm_2,T5,BadSummary,What do parametric models have on number of parameters?,fixed size,3002
56,4928,slp_chapter5_5,midterm_2,T5,Best Condition - with Davinci,What is L1 regularization?,linear function of the weight values,4928
57,5081,chapter_27_1_3,1st midterm,GPT3,From raw text,"What is the gödel sentence?
",The gödel sentence is a sentence of the formal system that cannot be proved within that formal system.,5081
58,1737,chapter19_4,midterm_2,GPT3,Fewshot,"What is the split data into training and test set?
","The split data into training and test set is the process of separating the data into two sets, a training set and a test set.",1737
59,710,slp_chapter6_8,midterm_2,GPT3,GoodSummary,"What is skip-gram with negative sampling, sgns?
",Sgns is one of two algorithms in word2vec - static embeddings. (compared to dynamic contextual embeddings like the popular family of bert representations).,710
60,2839,chapter6_1,midterm_1,T5,BadSummary,What does the process of enforcing local consistency in each part of the constraint graph cause to be eliminated throughout the graph?,inconsistent values,2839
61,4139,chapter19_3,midterm_2,T5,Fewshot,Decision trees can often be what with interpretable results?,intuitive,4139
62,1490,chapter3_3,midterm_1,GPT3,Fewshot,"What is the best first search algorithm?
",The best first search algorithm expands with min(f(n)).,1490
63,5161,chapter_3_1_1,1st midterm,GPT3,From raw text,"What is the goal state in a search problem?
",The goal state in a search problem is the state that the agent is trying to reach.,5161
64,287,slp_chapter7_4,midterm_2,GPT3,Best Condition - with Davinci,"What is the difference between simple static word embeddings and the more powerful contextual embeddings?
",The difference between simple static word embeddings and the more powerful contextual embeddings is that the former does not utilize contextual information in the embedding and the latter does.,287
65,278,slp_chapter7_2,midterm_2,GPT3,Best Condition - with Davinci,"What is an example of a perceptron?
",An example of a perceptron is a machine that recognizes numbers written in digits.,278
66,1888,slp_chapter6_12,midterm_2,GPT3,Fewshot,"What task is used for evaluation of intrinsic similarity tasks that include context?
",The,1888
67,1976,chapter3_4,midterm_1,T5,GoodSummary,What runs DLS with increasing values of $l$?,**Iterative deepening search,1976
68,6249,chapter_27_1_4,1st midterm,T5,From GPT-3 generated summary,What percentage of the time is the interrogator fooled?,30%,6249
69,5097,chapter_27_2_1,1st midterm,GPT3,From raw text,"Who is a proponent of biological naturalism?
","John searle is a proponent of biological naturalism, which is the belief that mental states are high-level emergent features that are caused by low-level physical processes in the neurons.",5097
70,5702,chapter_2_4_3,1st midterm,T5,From raw text,When do one or more illuminated red regions appear in the forward-facing camera image?,when the car in front initiates braking,5702
71,1424,slp_chapter6_8,midterm_2,GPT3,Zero,"What is the difference between gpt-3 and gpt-2?
","Gpt-3 is the successor to the gpt-2 model, which was trained on a much smaller corpus of text.",1424
72,6233,chapter_27_1,1st midterm,T5,From GPT-3 generated summary,Who introduced a distinction between weak AI and strong AI?,John Searle,6233
73,5124,chapter_2_3_2,1st midterm,GPT3,From raw text,"What are the differences between single-agent and multiagent environments?
","The distinction between single-agent and multiagent environments may seem simple enough. for example, an agent solving a crossword puzzle by itself is clearly in a single-agent environment, whereas an agent playing chess is in a two-agent environment. however, there are some subtle issues. first, we have described how an entity may be viewed as an agent, but we have not explained which entities must be viewed as agents. does an agent (the taxi driver for example) have to treat an object (another vehicle) as an agent, or can it be treated merely as an object behaving according to the laws of physics, analogous to waves at the beach or leaves blowing in the wind? the key distinction is whether ’s behavior is best described as maximizing a",5124
74,3507,chapter19_3,midterm_2,T5,Zero,What shows the proportion of correct decisions on a test set with the training set size?,learning curve,3507
75,3828,chapter3_4,midterm_1,T5,Fewshot,What is the frontier in DFS?,a stack,3828
76,5146,chapter_2_4_6,1st midterm,GPT3,From raw text,"What is the most important distinction between the learning element and the performance element?
","The most important distinction between the learning element and the performance element is that the former is responsible for making improvements, and the latter is responsible for selecting external actions.",5146
77,362,chapter27_2,midterm_1,GPT3,GoodSummary,"What is the problem with there being no direct evidence about human mental states?
",Turing notes there is no direct evidence about human mental states.,362
78,4241,slp_chapter7_1,midterm_2,T5,Fewshot,What is the output of a non-linear function f applied to the unit's input z?,The activation value,4241
79,484,chapter16_2,midterm_2,GPT3,GoodSummary,"What is a utility theory?
",A utility theory is a theory that explains how preferences between complex lotteries are related to preferences between the underlying states of those lotteries.,484
80,1183,chapter22_2,midterm_2,GPT3,Zero,"What is passive temporal difference learning?
","Passive temporal difference learning is a technique that learns utility estimates using temporal differences, without needing a transition model.",1183
81,4843,chapter19_5,midterm_2,T5,Best Condition - with Davinci,What can a function learn in function learning do?,make a decision,4843
82,3753,chapter2_1,midterm_1,T5,Fewshot,What is the best way to fill out the table?,have the vacuum cleaner move randomly until it finds dirt,3753
83,3505,chapter19_3,midterm_2,T5,Zero,Decision trees can often be what?,very intuitive,3505
84,2402,chapter13_3,midterm_2,T5,GoodSummary,What can be used to bound complexity of Bayes nets?,Tree width,2402
85,6084,chapter_2_2,1st midterm,GPT3,From GPT-3 generated summary,"What is a performance measure? 
",A performance measure is a measure of an agent’s performance.,6084
86,6006,chapter_3_4_6,1st midterm,T5,From raw text,The space and time complexities are bounded by what?,the size of the state space,6006
87,988,slp_chapter6_2,midterm_2,GPT3,BadSummary,"This is a very abstract question. 

review what is a word?
","A word is a sequence of one or more letters.

what is the most important difference between a sentence and a word?
",988
88,2986,chapter19_1,midterm_2,T5,BadSummary,"What type of learning does an agent learn from series of reinforcements, rewards and punishments?",Reinforcement learning,2986
89,1100,chapter6_2,midterm_1,GPT3,Zero,"What happens if the domain of x_i is changed?
","If the domain of x_i is changed (i.e. made smaller), then all arcs (x_k, x_i) in which x_i and x_k are neighbors are added to the queue.",1100
90,6325,chapter_2_2_3,1st midterm,T5,From GPT-3 generated summary,What is removed from the lowly dung beetle's nest?,ball of dung,6325
91,6413,chapter_3_3_3,1st midterm,T5,From GPT-3 generated summary,What can we compromise and check for?,cycles,6413
92,951,slp_chapter5_6,midterm_2,GPT3,BadSummary,"What is a maxent classifier?
",A maxent classifier is a type of classifier that uses a softmax function to assign a probability to each of the k classes.,951
93,3097,slp_chapter6_8,midterm_2,T5,BadSummary,What does Word2vec skip-gram?,Treat the target word and a neighboring context word as positive examples,3097
94,1671,chapter12_6,midterm_2,GPT3,Fewshot,"What is a bayesian classifier?
",A bayesian classifier is a probability distribution that is sometimes called a naive bayes model.,1671
95,2342,SLP_chapter3_4,midterm_2,T5,GoodSummary,What can be done implicitly?,Build vocabulary,2342
96,5078,chapter_27_1_2,1st midterm,GPT3,From raw text,"Are programs currently capable of doing all of these things?
","Programs are currently capable of doing some of these things, but not all of them.",5078
97,3718,slp_chapter6_12,midterm_2,T5,Zero,What are the three datasets commonly used for evaluation?,"WordSim-353, SimLex-999, and TOEFL",3718
98,133,SLP_chapter3_1,midterm_2,GPT3,Best Condition - with Davinci,"What is the more general case where we do not know the previous history of the system?
","The more general case where we do not know the previous history of the system is where we can use the markov assumption, which states that the probability of the current state is dependent only on the current state and not the previous states.",133
99,3591,slp_chapter5_1,midterm_2,T5,Zero,What model can generate new examples from a given set of training data?,generative model,3591
100,5199,chapter_3_3_4,1st midterm,GPT3,From raw text,"1
",To,5199
101,1178,chapter22_1,midterm_2,GPT3,Zero,"What are the two main approaches to reinforcement learning?
",The two main approaches to reinforcement learning are model-based and model-free.,1178
102,3331,chapter7_5,midterm_1,T5,Zero,What are sentences that are valid if they are true in all models called?,tautologies,3331
103,3005,slp_chapter4_5,midterm_2,T5,BadSummary,What measures percentage of items that were predicted positive that are actually positive?,Precision,3005
104,6186,chapter_3_4_3,1st midterm,GPT3,From GPT-3 generated summary,"What is depth-first search?
",Depth-first search expands the deepest node in the frontier first.,6186
105,3953,chapter7_4,midterm_1,T5,Fewshot,Propositional logic is what?,co-NP-complete,3953
106,925,slp_chapter4_6,midterm_2,GPT3,BadSummary,"What is the model assign probability to each sentence?
",The model assigns probability to each sentence.,925
107,1596,chapter7_5,midterm_1,GPT3,Fewshot,"
","
",1596
108,647,slp_chapter5_2,midterm_2,GPT3,GoodSummary,"What is logistic regression?
",Logistic regression is a supervised learning model.,647
109,1449,chapter27_1,midterm_1,GPT3,Fewshot,"What is the good old-fashioned ai (gofai) approach?
",The gofai approach corresponds to the simplest logical agent.,1449
110,2267,chapter22_4,midterm_2,T5,GoodSummary,"What is a common problem, but can be solved by experience replay?",Catastrophic forgetting,2267
111,6459,chapter_3_4_6,1st midterm,T5,From GPT-3 generated summary,What algorithm is guaranteed to find the shortest path to a goal state?,Breadth-first search,6459
112,117,chapter12_5,midterm_2,GPT3,Best Condition - with Davinci,"What is the general version of bayes' rule?
",The general version of bayes' rule is applicable for any multivalued variable.,117
113,986,slp_chapter6_1,midterm_2,GPT3,BadSummary,"What is lexical decomposition?
",Lexical decomposition is the process of breaking down a word into smaller words to get to the root of its meaning.,986
114,994,slp_chapter6_8,midterm_2,GPT3,BadSummary,"What is word2vec?
",Word2vec is a way of learning the probability of a word occurring close to another word.,994
115,604,chapter19_6,midterm_2,GPT3,GoodSummary,"Could we take advantage of parallel vector operations with some cpu's, making ""m"" itself a hyperparameter?
","We could take advantage of parallel vector operations with some cpu's, making ""m"" itself a hyperparameter.",604
116,5918,chapter_3_3_4,1st midterm,T5,From raw text,What are considered with respect to some measure of the problem difficulty?,Time and space complexity,5918
117,1520,chapter5_3,midterm_1,GPT3,Fewshot,"Given optimal examination, what is the runtime of the alpha-beta pruning algorithm?
","Given optimal examination, the runtime of the alpha-beta pruning algorithm is o(b^{d/2}).",1520
118,2933,chapter12_4,midterm_2,T5,BadSummary,What can help reduce the size of the domain representation and complexity of the inference problem?,independence assertions,2933
119,2,chapter16_3,midterm_1,GPT3,Best Condition - with Davinci,"What is the expected utility?

","The expected utility is the utility of an object and the standard lottery, adjusted until the agent is indifferent between the two, and you get the expected utility.",2
120,6119,chapter_2_4_3,1st midterm,GPT3,From GPT-3 generated summary,"What is a sensor model?
",A sensor model is a model of how the state of the world is mapped to the agent's percepts.,6119
121,4100,chapter13_1,midterm_2,T5,Fewshot,What does each node correspond to?,random variable,4100
122,3300,chapter6_3,midterm_1,T5,Zero,"What chooses the next variable to examine based on the variable with the fewest ""legal"" values remaining?",The MRV heuristic,3300
123,5333,chapter_1_1_5,1st midterm,T5,From raw text,What is the problem of achieving agreement between our true preferences and the objective we put into the machine called?,value alignment problem,5333
124,244,slp_chapter5_1,midterm_2,GPT3,Best Condition - with Davinci,"What is a generative model?
",A generative model is a model that can be used to understand what dogs look like and what cats look like.,244
125,6450,chapter_3_4_5,1st midterm,T5,From GPT-3 generated summary,What is an algorithm that starts at an initial state and searches forward and backwards simultaneously in the hope that the two searches will meet?,Bidirectional search,6450
126,6150,chapter_3_3,1st midterm,GPT3,From GPT-3 generated summary,"What is a search tree?
",A search tree is a tree that shows the possible paths that could be taken to reach a goal state.,6150
127,2729,chapter27_2,midterm_1,T5,BadSummary,"What is the usual to have polite convention that everyone thinks - Searle rejects polite convention: Chinese room does same as computer,",Turing,2729
128,2764,chapter2_4,midterm_1,T5,BadSummary,What does the agent need if it wants to walk?,legs,2764
129,5289,chapter_1_1_3,1st midterm,T5,From raw text,What does the theory of probability not do?,generate intelligent behavior,5289
130,3342,chapter16_3,midterm_2,T5,Zero,What is it helpful to establish a scale on which utilities can be recorded and compared for any particular problem?,utility assessment,3342
131,1798,slp_chapter5_3,midterm_2,GPT3,Fewshot,"What is conditional maximum likelihood estimation?
","Conditional maximum likelihood estimation is used to choose the parameters w,b that maximize the log probability of the true y labels in the training data given the observations x.",1798
132,5178,chapter_3_3_2,1st midterm,GPT3,From raw text,"What is a node in a search tree represented by?
","A node in a search tree is represented by a data structure with four components: state, parent, action, and path-cost",5178
133,209,slp_chapter4_3,midterm_2,GPT3,Best Condition - with Davinci,"What is the difference between removing duplicate words and concatenating the documents into a single document?
","The difference between removing duplicate words and concatenating the documents into a single document is that removing duplicate words removes duplicate words in the documents, whereas concatenating the documents into a single document concatenates the documents into a single document, without removing duplicate words.",209
134,697,slp_chapter6_2,midterm_2,GPT3,GoodSummary,"What are vectors for representing words called?
",Vectors for representing words are called embeddings.,697
135,4659,chapter12_1,midterm_2,T5,Best Condition - with Davinci,What does the agent's knowledge provide in the relevant sentences?,degree of belief,4659
136,1301,slp_chapter4_3,midterm_2,GPT3,Zero,"What is the difference between a naive bayes classifier and a maximum entropy classifier?
","A naive bayes classifier is a classifier that assumes that the features are conditionally independent given the class, while a maximum entropy classifier is a classifier that assumes that the features are conditionally dependent given the class.",1301
137,607,chapter19_6,midterm_2,GPT3,GoodSummary,"What is multivariable not much more complicated than linear regression?
",Multivariable,607
138,2406,chapter13_3,midterm_2,T5,GoodSummary,What does O(n?? 2) do?,reduce time complexity,2406
139,6155,chapter_3_3_1,1st midterm,GPT3,From GPT-3 generated summary,"What is the algorithm's goal?
",The algorithm's goal is to return a node that represents a path to a goal.,6155
