Download Latest AIP-210 Dumps with Authentic Real Exam QA’s [Q41-Q58]

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Download Latest AIP-210 Dumps with Authentic Real Exam Questions

Authentic AIP-210 Exam Dumps PDF – Jul-2024 Updated

NO.41 In a self-driving car company, ML engineers want to develop a model for dynamic pathing. Which of following approaches would be optimal for this task?

Dijkstra Algorithm

Reinforcement learning

Supervised Learning.

Unsupervised Learning

NO.42 Which of the following statements are true regarding highly interpretable models? (Select two.)

They are usually binary classifiers.

They are usually easier to explain to business stakeholders.

They are usually referred to as “black box” models.

They are usually very good at solving non-linear problems.

They usually compromise on model accuracy for the sake of interpretability.

NO.43 Your dependent variable Y is a count, ranging from 0 to infinity. Because Y is approximately log-normally distributed, you decide to log-transform the data prior to performing a linear regression.
What should you do before log-transforming Y?

Add 1 to all of the Y values.

Divide all the Y values by the standard deviation of Y.

Explore the data for outliers.

Subtract the mean of Y from all the Y values.

NO.44 Normalization is the transformation of features:

By subtracting from the mean and dividing by the standard deviation.

Into the normal distribution.

So that they are on a similar scale.

To different scales from each other.

NO.45 In which of the following scenarios is lasso regression preferable over ridge regression?

The number of features is much larger than the sample size.

There are many features with no association with the dependent variable.

There is high collinearity among some of the features associated with the dependent variable.

The sample size is much larger than the number of features.

NO.46 What is the primary benefit of the Federated Learning approach to machine learning?

It does not require a labeled dataset to solve supervised learning problems.

It protects the privacy of the user’s data while providing well-trained models.

It requires less computation to train the same model using a traditional approach.

It uses large, centralized data stores to train complex machine learning models.

NO.47 Personal data should not be disclosed, made available, or otherwise used for purposes other than specified with which of the following exceptions? (Select two.)

If it is for a good cause.

If it was collected accidentally.

If it was requested by the authority of law.

If it was with consent of the person it is collected from.

If the data is only collected once.

NO.48 Which of the following is the correct definition of the quality criteria that describes completeness?

The degree to which all required measures are known.

The degree to which a set of measures are equivalent across systems.

The degree to which a set of measures are specified using the same units of measure in all systems.

The degree to which the measures conform to defined business rules or constraints.

NO.49 Which of the following best describes distributed artificial intelligence?

It does not require hyperparemeter tuning because the distributed nature accounts for the bias.

It intelligently pre-distributes the weight of starting a neural network.

It relies on a distributed system that performs robust computations across a network of unreliable nodes.

It uses a centralized system to speak to decentralized nodes.

NO.50 You are developing a prediction model. Your team indicates they need an algorithm that is fast and requires low memory and low processing power. Assuming the following algorithms have similar accuracy on your data, which is most likely to be an ideal choice for the job?

Deep learning neural network

Random forest

Ridge regression

Support-vector machine

NO.51 Which three security measures could be applied in different ML workflow stages to defend them against malicious activities? (Select three.)

Disable logging for model access.

Launch ML Instances In a virtual private cloud (VPC).

Monitor model degradation.

Use data encryption.

Use max privilege to control access to ML artifacts.

Use Secrets Manager to protect credentials.

NO.52 Which of the following sentences is TRUE about the definition of cloud models for machine learning pipelines?

Data as a Service (DaaS) can host the databases providing backups, clustering, and high availability.

Infrastructure as a Service (IaaS) can provide CPU, memory, disk, network and GPU.

Platform as a Service (PaaS) can provide some services within an application such as payment applications to create efficient results.

Software as a Service (SaaS) can provide AI practitioner data science services such as Jupyter notebooks.

NO.53 Which of the following text vectorization methods is appropriate and correctly defined for an English-to-Spanish translation machine?

Using TF-IDF because in translation machines, we do not care about the order of the words.

Using TF-IDF because in translation machines, we need to consider the order of the words.

Using Word2vec because in translation machines, we do not care about the order of the words.

Using Word2vec because in translation machines, we need to consider the order of the words.

NO.54 For a particular classification problem, you are tasked with determining the best algorithm among SVM, random forest, K-nearest neighbors, and a deep neural network. Each of the algorithms has similar accuracy on your data. The stakeholders indicate that they need a model that can convey each feature’s relative contribution to the model’s accuracy. Which is the best algorithm for this use case?

Deep neural network

K-nearest neighbors

Random forest

SVM

NO.55 Which database is designed to better anticipate and avoid risks of AI systems causing safety, fairness, or other ethical problems?

Asset

Code Repository

Configuration Management

Incident

NO.56 When working with textual data and trying to classify text into different languages, which approach to representing features makes the most sense?

Bag of words model with TF-IDF

Bag of bigrams (2 letter pairs)

Word2Vec algorithm

Clustering similar words and representing words by group membership

NO.57 When should you use semi-supervised learning? (Select two.)

A small set of labeled data is available but not representative of the entire distribution.

A small set of labeled data is biased toward one class.

Labeling data is challenging and expensive.

There is a large amount of labeled data to be used for predictions.

There is a large amount of unlabeled data to be used for predictions.

NO.58 Which of the following are true about the transform-design pattern for a machine learning pipeline? (Select three.) It aims to separate inputs from features.

It encapsulates the processing steps of ML pipelines.

It ensures reproducibility.

It represents steps in the pipeline with a directed acyclic graph (DAG).

It seeks to isolate individual steps of ML pipelines.

It transforms the output data after production.

CertNexus AIP-210 Exam Syllabus Topics:

Topic	Details
Topic 1	Address business risks, ethical concerns, and related concepts in training and tuning Work with textual, numerical, audio, or video data formats
Topic 2	Design machine and deep learning models Explain data collection transformation process in ML workflow
Topic 3	Identify potential ethical concerns Analyze machine learning system use cases
Topic 4	Recognize relative impact of data quality and size to algorithms Engineering Features for Machine Learning
Topic 5	Transform numerical and categorical data Address business risks, ethical concerns, and related concepts in operationalizing the model