Open the auxiliary access

Firefly Open Source Community

   Login   |   Register   |
New_Topic
Firefly Open Source Community › Core Board › iCore-3568JQ› Exam AIP-210 Reviews & AIP-210 New Study Questions ...
New Topic
Print Previous Topic Next Topic

[General] Exam AIP-210 Reviews & AIP-210 New Study Questions

louston976

128

Credits

0

Prestige

0

Contribution

registered members

Rank: 2

Credits
128

【General】 Exam AIP-210 Reviews & AIP-210 New Study Questions

Posted at before yesterday 10:59      View：6 | Replies：0        Print      Only Author   [Copy Link] 1#
BONUS!!! Download part of ValidVCE AIP-210 dumps for free: https://drive.google.com/open?id=1G2cExx5ydqGKhLgDOf2EIjVE6DNE-LS7
ValidVCE provides the three most convenient formats to prepare for AIP-210 exam dumps. It offers a desktop practice test, web based practice test and pdf file. Therefore, feel free to go through CertNexus Certified Artificial Intelligence Practitioner (CAIP) (AIP-210) exam dumps. Each of the three formats is downloaded to all android devices. Therefore, there's no reason to download an additional application to access web-based or desktop-based practice tests.
To let the client be familiar with the atmosphere of the AIP-210 exam we provide the function to stimulate the exam and the timing function of our AIP-210 study materials to adjust your speed to answer the questions. We provide the stimulation, the instances and the diagrams to explain the hard-to-understand contents of our AIP-210 Study Materials. For these great merits we can promise to you that if you buy our AIP-210 study materials you will pass the test without difficulties.
AIP-210 New Study Questions - AIP-210 Download DemoCandidates who pass AIP-210 Certification prove their worth in the CertNexus field. The CertNexus Certified Artificial Intelligence Practitioner (CAIP) certification is proof of their competence and skill. This skill is highly useful in big CertNexus companies that facilitate a candidate's career. To get certified, it is very important that you pass the CertNexus Certified Artificial Intelligence Practitioner (CAIP) certification exam to prove your skills to the tech company. For this task, you require high-quality and accurate prep material to help you out. And many people don't get reliable material and ultimately fail. Failure leads to a loss of time and money.
CertNexus AIP-210 Exam Syllabus Topics:
TopicDetails
Topic 1
  • Understanding the Artificial Intelligence Problem
  • Analyze the use cases of ML algorithms to rank them by their success probability
Topic 2
  • Address business risks, ethical concerns, and related concepts in training and tuning
  • Work with textual, numerical, audio, or video data formats
Topic 3
  • Design machine and deep learning models
  • Explain data collection
  • transformation process in ML workflow

CertNexus Certified Artificial Intelligence Practitioner (CAIP) Sample Questions (Q45-Q50):NEW QUESTION # 45
Which of the following best describes distributed artificial intelligence?
  • A. It uses a centralized system to speak to decentralized nodes.
  • B. It intelligently pre-distributes the weight of starting a neural network.
  • C. It does not require hyperparemeter tuning because the distributed nature accounts for the bias.
  • D. It relies on a distributed system that performs robust computations across a network of unreliable nodes.
Answer: D
Explanation:
Distributed artificial intelligence (DAI) is a subfield of artificial intelligence that studies how multiple intelligent agents can coordinate and cooperate to achieve a common goal or solve a complex problem. DAI relies on a distributed system that performs robust computations across a network of unreliable nodes, such as sensors, robots, or humans. DAI can handle large-scale, dynamic, and uncertain environments that are beyond the capabilities of a single agent. References: [Distributed artificial intelligence - Wikipedia], [Distributed Artificial Intelligence: An Overview]

NEW QUESTION # 46
Which of the following algorithms is an example of unsupervised learning?
  • A. Random forest
  • B. Neural networks
  • C. Ridge regression
  • D. Principal components analysis
Answer: D
Explanation:
Unsupervised learning is a type of machine learning that involves finding patterns or structures in unlabeled data without any predefined outcome or feedback. Unsupervised learning can be used for various tasks, such as clustering, dimensionality reduction, anomaly detection, or association rule mining. Some of the common algorithms for unsupervised learning are:
* Principal components analysis: Principal components analysis (PCA) is a method that reduces the dimensionality of data by transforming it into a new set of orthogonal variables (principal components) that capture the maximum amount of variance in the data. PCA can help simplify and visualize high- dimensional data, as well as remove noise or redundancy from the data.
* K-means clustering: K-means clustering is a method that partitions data into k groups (clusters) based on their similarity or distance. K-means clustering can help discover natural or hidden groups in the data, as well as identify outliers or anomalies in the data.
* Apriori algorithm: Apriori algorithm is a method that finds frequent itemsets (sets of items that occur together frequently) and association rules (rules that describe how items are related or correlated) in transactional data. Apriori algorithm can help discover patterns or insights in the data, such as customer behavior, preferences, or recommendations.

NEW QUESTION # 47
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?
  • A. Explore the data for outliers.
  • B. Subtract the mean of Y from all the Y values.
  • C. Add 1 to all of the Y values.
  • D. Divide all the Y values by the standard deviation of Y.
Answer: C
Explanation:
Explanation
Before log-transforming Y, we should add 1 to all of the Y values. This is because log transformation is undefined for zero or negative values, and some of the Y values may be zero. Adding 1 to all of the Y values can avoid this problem and ensure that the log transformation is valid and meaningful. Adding 1 to all of the Y values is also known as a log-plus-one transformation.

NEW QUESTION # 48
You have a dataset with thousands of features, all of which are categorical. Using these features as predictors, you are tasked with creating a prediction model to accurately predict the value of a continuous dependent variable. Which of the following would be appropriate algorithms to use? (Select two.)
  • A. Logistic regression
  • B. Ridge regression
  • C. Lasso regression
  • D. K-nearest neighbors
  • E. K-means
Answer: B,C
Explanation:
Lasso regression and ridge regression are both types of linear regression models that can handle high- dimensional and categorical data. They use regularization techniques to reduce the complexity of the model and avoid overfitting. Lasso regression uses L1 regularization, which adds a penalty term proportional to the absolute value of the coefficients to the loss function. This can shrink some coefficients to zero and perform feature selection. Ridge regression uses L2 regularization, which adds a penalty term proportional to the square of the coefficients to the loss function. This can shrink all coefficients towards zero and reduce multicollinearity. References: [Lasso (statistics) - Wikipedia], [Ridge regression - Wikipedia]

NEW QUESTION # 49
Which of the following is a type 1 error in statistical hypothesis testing?
  • A. The null hypothesis is true, but is rejected.
  • B. The null hypothesis is false and is rejected.
  • C. The null hypothesis is true and fails to be rejected.
  • D. The null hypothesis is false, but fails to be rejected.
Answer: A
Explanation:
Explanation
A type 1 error in statistical hypothesis testing is when the null hypothesis is true, but is rejected. This means that the test falsely concludes that there is a significant difference or effect when there is none. The probability of making a type 1 error is denoted by alpha, which is also known as the significance level of the test. A type 1 error can be reduced by choosing a smaller alpha value, but this may increase the chance of making a type 2 error, which is when the null hypothesis is false but fails to be rejected. References: [Type I and type II errors - Wikipedia], [Type I Error and Type II Error - Statistics How To]

NEW QUESTION # 50
......
In our study, we found that many people have the strongest ability to use knowledge for a period of time at the beginning of their knowledge. As time goes on, memory fades. Our AIP-210 study materials are designed to help users consolidate what they have learned, will add to the instant of many training, the user can test their learning effect in time after finished the part of the learning content, have a special set of wrong topics in our AIP-210 Study Materials, enable users to find their weak spot of knowledge in this function, iterate through constant practice, finally reach a high success rate.
AIP-210 New Study Questions: https://www.validvce.com/AIP-210-exam-collection.html
What's more, part of that ValidVCE AIP-210 dumps now are free: https://drive.google.com/open?id=1G2cExx5ydqGKhLgDOf2EIjVE6DNE-LS7
https://www.passtip.net
Reply

Use props Report

Return to List
High mode
B Color Image Link Quote Code Smilies
You need to log in before you can reply Login | Register

This forum Credits Rules

  •  

Service Hotline : (+86)18688117175
Contact us
E-mail : global@t-firefly.com
Copyright © 2014-2022, FIREFLY TECHNOLOGY CO.,LTD. All Rightts Reserved. 粤ICP备14022046号-2
Quick Reply Back to top Back to list