AI exam 2 practice exam

Re-organize figure A, B, C below into correct order to represent Dimensionality Reduction:

C (3d), A(2d), B(1d)

what is computer vision?

CNN based algorithms focusing on understanding images/videos by performing tasks such as object classification, detection, and segmentation

Hidden layer stacking order

Convolution layer Activation layer Pooling layer Fully connected layer Final activation layer

True or False: In reinforcement learning, agent lives in a static environment and thus learning to take actions and find the best policy without analyzing the state of its environment

False, it is constantly analyzing the state of its environment

reinforcement learning part 4

Update policy to maximize a reward

logistic regression definition

a classification learning algorithm based on the concept of probability, typically by using the sigmoid function

activation function definition

a function used to decide whether the output exceeds a certain threshold and gives on or off as an output

linear regression definition

a regression learning algorithm that uses a linear combination of features (x) and parameters ( w and b) to build a prediction model

"If a patient is prescribed steroid cream, then the patient is 70% likely of buying antihistamines." The consequent and antecedent in the above sentence (in order) are a) Antihistamines, steroid cream b) Steroid cream, patient c) Steroid cream, antihistamines d) Antihistamines, patient

a) antihistamines, steroid cream

Which of the following terminology is not an element of causal inference? a) Document classification b) Features in each patient c) Observational data d) Treatment assignment

a) document classification

Consider the following sentence as an input in NLP: "I like listening to pop music". How many possible outputs are there if Trigram language model is used? a) Four b) Three c) Five d) Two

a) four

The following functions are suitable as activation functions, except: a) Linear regression b) Sigmoid function c) Tanh function d) ReLU function

a) linear regression

Natural Language Processing is a subfield of AI and an intersection of the following fields: a) Linguistics and computer science b) Neuroscience and sociology c) Neuroscience and computer science d) Sociology and linguistics

a) linguistics and computer science

The following statement is a potential factor contributing the difficulty of NLP progress, except: a) Natural language is not part of computer vision b) Natural language sentences are infinite c) Natural language is ambiguous d) Natural language has complex representations

a) natural language is not a part of computer vision

The following terminology describes language model as the basis of NLP, except: a) Perceptron b) N-gram c) Word2Vec d) Bag-of-words

a) perceptron

Which of the following layer that does not exist in recurrent neural network? a) Pooling layer b) Hidden layer c) Input layer d) Output layer

a) pooling layer

The following application is suitable for CNN, except: a) Speech recognition b) Computer vision c) Object recognition d) Face recognition

a) speech recognition

Which of the following is not considered a challenge in Federated Learning? a) Systems homogeneity b) Expensive communication c) Statistical heterogeneity d) Privacy concerns

a) systems homogeneity

main challenge of CV in the field of healthcare

access to a large and labeled data set that is currently being mitigated with data augmentation technique

6 elements of RL

agent environment state action policy rewards

reinforcement learning part 1

agent placed in an environment to take an action

Gradient Descent definition

an iterative process to minimize the cost value within a cost function (minimizing errors)

Reinforcement learning part 2

at every action the state of the environment changes

The following terminology/description depicts deep neural networks, except: a) Networks trained by deep learning b) A simple model of biological neuron in an artificial neural network c) Consists of multiple hidden layers and output layers d) Example algorithms include convolutional and recurrent neural networks

b) a simple model of biological neuron in an artificial neural network

Which of the following scenarios describes the challenge of implementing causal inference? a) Factual outcomes are not typically observed b) Counterfactual outcomes are not typically observed c) Observational data from patients lack features in each patient d) Causal inference is a simple machine learning problem

b) counterfactual outcomes are not typically observed

Which of the following layer belongs to classification step in CNN? a) Convolution layer b) Fully connected layer c) Pooling layer d) Input layer

b) fully connected layer

Variables that are multiplied by input signals and give importance to various input signals are called a) Step function b) Weights c) Bias d) Activation function

b) weights

The following Federated Learning terminology describes FL Clients, except: a) Mobile devices b) IoT devices c) Server d) Data silos

c) server

The following MRI data format is suitable for applying machine learning algorithm to predict MCI a) phosphorus imaging b) magnetic resonance spectroscopy c) structured t1-weighted d) diffusion tensor imaging

c) structured t1-weighted

Which of the following is not an element of Reinforcement Learning? a) Agent b) Environment c) Training data d) Rewards

c) training data

disadvantages of deep learning

computationally intensive and expensive considered opaque or black box (difficult to understand the output) requires large data to train

Which of the following statements is false regarding association rule mining? a) An association rule learning has two parts, resembling 'if/then' statements b) Association rules are created from analyzing database based on frequency of 'if/then' statements c) Support (s) metric measures how frequently 'if/then' relationship appears in a database d) Confidence (c) metric measures how frequently 'if/then' relationship appears in a database

d) Confidence (c) metric measures how frequently 'if/then' relationship appears in a database

The process to reduce the size or dimension of dataset while maintaining variation within the data as much as possible is a definition of: a) Features b) Curse of Dimensionality c) instances or Observations d) Dimensionality Reduction

d) dimensionality reduction

The following layer can be found within the stacking hidden layers in CNN, except: a) Pooling layer b) Convolution layer c) Fully connected layer d) Input layer

d) input layer

Which of the following describes cross-silo federated learning? a) Multiple patients b) Multiple computers c) Multiple mobile devices d) Multiple institutions

d) multiple institutions

A simple model of biological neuron in an artificial neural network is the definition of: a) Activation function b) Convolutional neural networks c) Deep learning d) Perceptron

d) perceptron

Which statement best describes the curse of dimensionality phenomenon? a) The algorithm fails to identify interesting relations between features due to unstructured database b) Failure in learning algorithms due to insufficient number of of feature dimension within datasets c) The algorithm cannot learn effectively due to the number of observations exceeding the total number of features d) The algorithm cannot learn effectively due to the number of features exceeding the total number of observations

d) the algorithm cannot learn effectively due to the number of features exceeding the total number of observations

definition of high dimensional data

data in which the number of features is greater than the number of observations (p>n)

definition of low dimensional data

data in which the number of observations far outnumbers the number of features

linear regression in neural networks

each neuron is a linear combination of inputs (x), weights (w), and biases (b)

true or false: In bag-of-words language model, the order and position of words relative to one another is the outmost important

false

true or false: Neural network is a sub-field of deep learning in the overall artificial intelligence hierarchy

false

true or false: Pre-processing step in NLP such as data cleaning typically takes the least amount of project time

false

true or false: Randomized Control Trials (RCTs) are considered superior compared to Adaptive Clinical Trials due to implementation of causal inference principles

false

true or false: Image recognition is one of the strong suits of RNN application

false, CNN

true or false: Convolutional neural networks only applicable to sequential data and are commonly used in voice recognition software

false, image data

True or False: Association rule learning is only suitable to handle numerical data

false, only categorical

true or false: Federated Learning allows direct raw data communication while distributed machine learning prevents this action

false, opposite

advantages of deep learning

features automatically selected considered robust and can handle variation applicable to diff data types scalable

output layer

final layer where prediction is

gradient descent neural networks

gauge accuracy in each iteration optimize w and b

elements of CNN

image data inputs and outputs independent parameter and weight sharing no recurrent connection

Elements of ANN

inputs text or tabular data inputs and outputs independent no parameter or weight sharing no recurrent connection

two machine learning algorithms that can be applied in Toxicology

kNN support vector machine

NLP impact in healthcare

machine translation speech recognition summarization topic modeling

example of CV in healthcare

medical imaging, flagging certain areas in imaging

A language terminology that focuses on the smallest units that have meanings are called a) Phonetics b) Syntax c) Semantics d) Morphology

morphology

What is federated learning?

multiple entities collaborate in solving a machine learning problem under the coordination of a central server. Raw data is stored locally and not exchanged or transferred.

The following terminology is an alias to artificial neural network, except: a) Feedforward neural networks b) Multilayer perceptrons c) Vanilla neural networks d) Recurrent neural networks

recurrent neural networks

association rule learning definition

rule based machine learning method for discovering interesting relations between variables in large databases

elements of RNN

sequence data outputs are dependent on what comes before them parameter and weight sharing recurrent connection

NLP impact in education

spam detection

NLP impact in business

spelling check personal assistant document classification hand writing recognition

activation function in neural network

sum at each neuron decides if the neuron is turned on or off

two ML algorithms that can be applied to predict MCI diagnosis

support vector machine, support vector regression

reinforcement learning part 3

the agent will analyze the state a take action suitable for that state

The following statements are considered as contributing factors for implementing artificial intelligence and machine learning in the field of toxicology, except:

the database containing chemical properties for investigational drugs is small and limited

goal of association rule learning

to identify strong rules discovered in databases using some measure of interestingness

True or False: A given dataset containing one hundred features with a total of sixty observations is considered high-dimensional data

true

true or false: Activation functions are computed at each node throughout the neural networks

true

true or false: Back-propagation includes adjusting weights to reduce error in perceptron model

true

true or false: Both linear and logistic regression attempt to minimize parameter w and b

true

true or false: Causal inference can be applied to improve individual treatment effects in patients that may be superior to group level treatment approach

true

true or false: Dimensionality reduction is a type of feature extraction technique

true

true or false: Gradient descent is an iterative process to minimize errors that is used in both linear and logistic regression

true

true or false: Perceptron model process implies a supervised learning algorithm that solves classification problem

true

true or false: Phonetics primarily focus on the sound or acoustic patterns in languages

true

true or false: Retrieving information about number of features without knowing the actual size of observations may lead to inaccurate dimensionality assessments

true

true or false: The dataset represented below is considered high-dimensional data 6 features, 3 observations

true

true or false: supervised learning algorithms typically produce higher accuracies when predicting Alzheimer's disease patients than patients with mild cognitive impairment versus healthy controls

true

true or false: tumor cell type and size are some examples of input features in study framework to test a PBPK model in tumor-bearing mice

true

logistic regression in neural networks

used within an activation function to determine whether the output of a neuron is on or off

An ordered list of scalar values in 1-D matrix or array shape and usually representation of attributes/features is a definition of: a) Matrix b) Tensor c) Vector d) Scalar

vector

factual outcomes

what it is actually observed

counterfactual outcomes

what would have happened

input layer

where data enters the network

hidden layer

where data is processed between the input and output layers