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CertNexus Valid AIP-210 Test Papers: CertNexus Certified Artificial Intelligence Practitioner (CAIP) - ITExamSimulator Authoritative Provider

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CertNexus AIP-210 Exam Syllabus Topics:

Topic
Details

Topic 1

Train, validate, and test data subsets
Training and Tuning ML Systems and Models

Topic 2

Recognize relative impact of data quality and size to algorithms
Engineering Features for Machine Learning

Topic 3

Transform numerical and categorical data
Address business risks, ethical concerns, and related concepts in operationalizing the model

Topic 4

Address business risks, ethical concerns, and related concepts in training and tuning
Work with textual, numerical, audio, or video data formats

Topic 5

Understanding the Artificial Intelligence Problem
Analyze the use cases of ML algorithms to rank them by their success probability

Topic 6

Design machine and deep learning models
Explain data collection
transformation process in ML workflow

CertNexus Certified Artificial Intelligence Practitioner (CAIP) Sample Questions (Q75-Q80):

NEW QUESTION # 75
Which two techniques are used to build personas in the ML development lifecycle? (Select two.)

A. Population regression
B. Population triage
C. Population variance
D. Population estimates
E. Population resampling

Answer: B,D

Explanation:
Personas are fictional characters that represent the potential users or customers of an ML system. Personas can help understand the needs, goals, preferences, and behaviors of the target audience, as well as design and evaluate the system from their perspective. Some of the techniques that are used to build personas in the ML development lifecycle are:
* Population estimates: Population estimates are statistical methods that estimate the size, characteristics, and distribution of a population based on a sample or a census. Population estimates can help identify and quantify the potential market segments and user groups for an ML system, as well as their demographics, locations, and behaviors.
* Population triage: Population triage is a process of prioritizing and selecting the most relevant and representative personas for an ML system based on some criteria or metrics. Population triage can help focus on the key user needs and scenarios, as well as avoid creating too many or too few personas.

NEW QUESTION # 76
Which of the following is NOT an activation function?

A. Hyperbolic tangent
B. Additive
C. ReLU
D. Sigmoid

Answer: B

Explanation:
Explanation
An activation function is a function that determines the output of a neuron in a neural network based on its input. An activation function can introduce non-linearity into a neural network, which allows it to model complex and non-linear relationships between inputs and outputs. Some of the common activation functions are:
Sigmoid: A sigmoid function is a function that maps any real value to a value between 0 and 1. It has an S-shaped curve and is often used for binary classification or probability estimation.
Hyperbolic tangent: A hyperbolic tangent function is a function that maps any real value to a value between -1 and 1. It has a similar shape to the sigmoid function but is symmetric around the origin. It is often used for regression or classification problems.
ReLU: A ReLU (rectified linear unit) function is a function that maps any negative value to 0 and any positive value to itself. It has a piecewise linear shape and is often used for hidden layers in deep neural networks.
Additive is not an activation function, but rather a term that describes a property of some functions. Additive functions are functions that satisfy the condition f(x+y) = f(x) + f(y) for any x and y. Additive functions are linear functions, which means they have a constant slope and do not introduce non-linearity.

NEW QUESTION # 77
R-squared is a statistical measure that:

A. Is the proportion of the variance for a dependent variable thaf' s explained by independent variables.
B. Combines precision and recall of a classifier into a single metric by taking their harmonic mean.
C. Represents the extent to which two random variables vary together.
D. Expresses the extent to which two variables are linearly related.

Answer: A

Explanation:
Explanation
R-squared is a statistical measure that indicates how well a regression model fits the data. R-squared is calculated by dividing the explained variance by the total variance. The explained variance is the amount of variation in the dependent variable that can be attributed to the independent variables. The total variance is the amount of variation in the dependent variable that can be observed in the data. R-squared ranges from 0 to 1, where 0 means no fit and 1 means perfect fit.

NEW QUESTION # 78
Which of the following is NOT a valid cross-validation method?

A. Bootstrapping
B. K-fold
C. Leave-one-out
D. Stratification

Answer: D

Explanation:
Explanation
Stratification is not a valid cross-validation method, but a technique to ensure that each subset of data has the same proportion of classes or labels as the original data. Stratification can be used in conjunction with cross-validation methods such as k-fold or leave-one-out to preserve the class distribution and reduce bias or variance in the validation results. Bootstrapping, k-fold, and leave-one-out are all valid cross-validation methods that use different ways of splitting and resampling the data to estimate the performance of a machine learning model.

NEW QUESTION # 79
Personal data should not be disclosed, made available, or otherwise used for purposes other than specified with which of the following exceptions? (Select two.)

A. If it was with consent of the person it is collected from.
B. If the data is only collected once.
C. If it was collected accidentally.
D. If it was requested by the authority of law.
E. If it is for a good cause.

Answer: A,D

Explanation:
Explanation
Personal data is any information that relates to an identified or identifiable individual, such as name, address, email, phone number, or biometric data. Personal data should not be disclosed, made available, or otherwise used for purposes other than specified, except with:
The consent of the person it is collected from: Consent is a clear and voluntary indication of agreement by the person to the processing of their personal data for a specific purpose. Consent can be given by a statement or a clear affirmative action, such as ticking a box or clicking a button.
The authority of law: The authority of law is a legal basis or obligation that requires or permits the processing of personal data for a legitimate purpose. For example, the authority of law could be a court order, a subpoena, a warrant, or a statute.

NEW QUESTION # 80
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