INTEREACTIVE AIP-210 TESTING ENGINE & PDF AIP-210 EXAM DUMP

Intereactive AIP-210 Testing Engine & Pdf AIP-210 Exam Dump

Intereactive AIP-210 Testing Engine & Pdf AIP-210 Exam Dump

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Tags: Intereactive AIP-210 Testing Engine, Pdf AIP-210 Exam Dump, AIP-210 Latest Exam Cram, Latest AIP-210 Exam Test, Reliable AIP-210 Study Notes

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CertNexus Certified Artificial Intelligence Practitioner (CAIP) Sample Questions (Q54-Q59):

NEW QUESTION # 54
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 requested by the authority of law.
  • B. If it was collected accidentally.
  • C. If the data is only collected once.
  • D. If it is for a good cause.
  • E. If it was with consent of the person it is collected from.

Answer: A,E

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 # 55
Which of the following tools would you use to create a natural language processing application?

  • A. AWS DeepRacer
  • B. DeepDream
  • C. NLTK
  • D. Azure Search

Answer: C

Explanation:
Explanation
NLTK (Natural Language Toolkit) is a Python library that provides a set of tools and resources for natural language processing (NLP). NLP is a branch of AI that deals with analyzing, understanding, and generating natural language texts or speech. NLTK offers modules for various NLP tasks, such as tokenization, stemming, lemmatization, parsing, tagging, chunking, sentiment analysis, named entity recognition, machine translation, text summarization, and more .


NEW QUESTION # 56
An AI practitioner incorporates risk considerations into a deployment plan and decides to log and store historical predictions for potential, future access requests.
Which ethical principle is this an example of?

  • A. Privacy
  • B. Transparency
  • C. Fairness
  • D. Safety

Answer: B

Explanation:
Explanation
Transparency is an ethical principle that describes the degree to which an AI system can provide clear and understandable information about its inputs, outputs, processes, and decisions. Transparency can help increase trust and confidence among users and stakeholders, as well as enable accountability and responsibility for the system's actions and outcomes. Logging and storing historical predictions for potential, future access requests is an example of transparency, as it can help provide evidence and explanation for the system's recommendations, as well as facilitate auditing and feedback.


NEW QUESTION # 57
Which of the following is TRUE about SVM models?

  • A. They can be used only for classification.
  • B. They can take the feature space into higher dimensions to solve the problem.
  • C. They use the sigmoid function to classify the data points.
  • D. They can be used only for regression.

Answer: B

Explanation:
Explanation
SVM models can use kernel functions to map the input data into higher-dimensional feature spaces, where linear separation is possible. This allows SVM models to handle non-linear problems effectively.
References: CertNexus Certified Artificial Intelligence Practitioner, Support vector machine - Wikipedia


NEW QUESTION # 58
Which of the following text vectorization methods is appropriate and correctly defined for an English-to-Spanish translation machine?

  • A. Using TF-IDF because in translation machines, we need to consider the order of the words.
  • B. Using Word2vec because in translation machines, we do not care about the order of the words.
  • C. Using Word2vec because in translation machines, we need to consider the order of the words.
  • D. Using TF-IDF because in translation machines, we do not care about the order of the words.

Answer: C

Explanation:
Explanation
Text vectorization is a technique that converts text into numerical vectors that can be used by machine learning models. Text vectorization can use different methods to represent text features, such as word frequency, word order, word meaning, or word context. Some of the common text vectorization methods are:
TF-IDF: TF-IDF (term frequency-inverse document frequency) is a method that assigns a weight to each word based on its frequency in a document and its rarity across a collection of documents. TF-IDF can capture the importance and relevance of words for a given topic or domain, but it does not consider the order or meaning of words.
Word2vec: Word2vec is a method that learns a vector representation for each word based on its context in a large corpus of text. Word2vec can capture the semantic and syntactic similarity and relationships among words, as well as preserve the order of words.
For an English-to-Spanish translation machine, using Word2vec would be appropriate and correctly defined, because in translation machines, we need to consider the order of the words, as well as their meaning and context.


NEW QUESTION # 59
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