Artificial Intelligence Question Bank - Class 10
48 Questions
0 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

What is the main purpose of the evaluation stage in the AI project cycle?

  • To ensure the model's outputs are accurate prior to deployment (correct)
  • To gather new data for further modeling
  • To create visualizations for data exploration
  • To minimize the time spent on data acquisition

    • Which of the following is NOT considered an authentic source for data acquisition?

  • Surveys
  • System Hacking (correct)
  • Sensors
  • Web Scraping

    • Which learning approach uses predefined rules programmed by humans?

  • Supervised Learning
  • Unsupervised Learning
  • Rule Based Approach (correct)
  • Reinforcement Learning

    • What is the testing dataset used for in AI modeling?

    <p>To evaluate the performance of the trained algorithm</p> Signup and view all the answers

    Which graphical representation is most suitable for displaying continuous data such as monthly exam scores?

    <p>Linear graph</p> Signup and view all the answers

    What are the 4Ws referred to in the problem canvases during the problem scoping stage?

    <p>Why, Who, What, Where</p> Signup and view all the answers

    Which stage focuses on understanding and preparing the problem before developing AI solutions?

    <p>Problem Scoping</p> Signup and view all the answers

    What term describes the layers in a neural network?

    <p>Hidden Layers</p> Signup and view all the answers

    What characterizes a rule-based approach in AI modeling?

    <p>The developer defines the patterns and relationships in the data.</p> Signup and view all the answers

    Which of the following best describes the significance of a problem statement template?

    <p>It provides a structured framework to identify the core issues.</p> Signup and view all the answers

    What is Goal 1 of the Sustainable Development Goals (SDGs)?

    <p>End poverty in all its forms everywhere.</p> Signup and view all the answers

    Which precaution should be considered when acquiring data for an AI project?

    <p>The data must be accurate and from authentic sources.</p> Signup and view all the answers

    What does the term 'data features' refer to in an AI project?

    <p>The type of data collected, which should be relevant.</p> Signup and view all the answers

    In the context of classification AI models, what type of data is primarily used?

    <p>When the data consists of labeled instances.</p> Signup and view all the answers

    What do the SDGs aim to achieve by 2030?

    <p>Ending poverty and ensuring sustainable development.</p> Signup and view all the answers

    What is a key element of a classification AI model?

    <p>It categorizes data into distinct labels based on parameters.</p> Signup and view all the answers

    What kind of data do regression models work on to make predictions?

    <p>Continuous data</p> Signup and view all the answers

    What is the primary purpose of the AI Project Cycle?

    <p>To provide a clear framework for project development</p> Signup and view all the answers

    Which of the following best describes the clustering process?

    <p>It divides data points into groups based on similarity.</p> Signup and view all the answers

    In the data exploration stage, what is primarily validated?

    <p>The data follows pre-defined specifications.</p> Signup and view all the answers

    Which of the following is NOT one of the five stages in the AI Project Cycle?

    <p>User Feedback</p> Signup and view all the answers

    What characterizes supervised learning?

    <p>Training with labeled input data</p> Signup and view all the answers

    Which of the following is NOT a feature of Artificial Neural Networks?

    <p>They require extensive manual feature extraction.</p> Signup and view all the answers

    What is the purpose of using historical data in regression analysis?

    <p>To understand the distribution movement and predict future outputs.</p> Signup and view all the answers

    How does the output layer function in an AI model with hidden layers?

    <p>It delivers the final result after transformations from hidden layers</p> Signup and view all the answers

    What distinguishes unsupervised learning from supervised learning in clustering?

    <p>Unsupervised learning identifies patterns without prior labeling.</p> Signup and view all the answers

    What is a benefit of dividing the AI project development into stages?

    <p>It simplifies understanding of the development process</p> Signup and view all the answers

    In supervised learning, what happens after the machine is trained?

    <p>It applies learned outcomes to new data examples</p> Signup and view all the answers

    Why is feature extraction important in Artificial Neural Networks?

    <p>It allows the model to automatically identify relevant attributes.</p> Signup and view all the answers

    In regression analysis, which is a common application?

    <p>Predicting future salary based on past earnings.</p> Signup and view all the answers

    Which stage of the AI Project Cycle involves gathering the necessary data for analysis?

    <p>Data Acquisition</p> Signup and view all the answers

    What does the term 'labelled data' mean in the context of supervised learning?

    <p>Data that is marked with known outcomes</p> Signup and view all the answers

    What is the primary objective of an unsupervised learning model?

    <p>To identify relationships, patterns, and trends in unlabeled data.</p> Signup and view all the answers

    Which of the following best exemplifies a classification algorithm?

    <p>Email spam detection based on training data.</p> Signup and view all the answers

    What is a key difference between classification and clustering algorithms?

    <p>Classification works on labeled data, while clustering works on unlabeled data.</p> Signup and view all the answers

    In regression analysis, what is typically being predicted?

    <p>Continuous variables and relationships between them.</p> Signup and view all the answers

    Which statement accurately describes the function of clustering in unsupervised learning?

    <p>It organizes unsorted information according to similarities and differences.</p> Signup and view all the answers

    What role does a mapping function serve in classification algorithms?

    <p>To link input variables to discrete output classes.</p> Signup and view all the answers

    What type of dataset does an unsupervised learning model primarily utilize?

    <p>Random and unlabeled dataset for pattern analysis.</p> Signup and view all the answers

    Which of the following tasks is NOT typically associated with unsupervised learning?

    <p>Predicting weather conditions based on past temperatures.</p> Signup and view all the answers

    What is the primary goal of classification in data analysis?

    <p>To separate data into multiple categorical classes</p> Signup and view all the answers

    Which of the following is an example of a classification algorithm?

    <p>Logistic regression</p> Signup and view all the answers

    How does regression differ from classification?

    <p>Regression models functions for continuous quantities whereas classification models functions for categories.</p> Signup and view all the answers

    What is a common way to evaluate the performance of regression algorithms?

    <p>Using root mean square error</p> Signup and view all the answers

    Which of the following statements about classification data is true?

    <p>Classification requires a model that predicts unordered data classes.</p> Signup and view all the answers

    What is the role of regression analysis in data science?

    <p>To identify numeric dependencies and predict continuous data</p> Signup and view all the answers

    Which goal relates to providing education through various technological approaches?

    <p>Quality Education</p> Signup and view all the answers

    In regression analysis, what is the main objective when developing a model?

    <p>To ensure the least possible error deviation</p> Signup and view all the answers

    Study Notes

    Artificial Intelligence - Question Bank - Class 10

    • AI Project Cycle Stages: Problem Scoping, Data Acquisition, Data Exploration, Modeling, Evaluation

    • Sustainable Development Goals (SDGs): A collection of 17 interconnected goals adopted by the UN in 2015 to end poverty, protect the planet, and ensure prosperity for all. Alternatively, the goals are a blueprint for a better and more sustainable future for all generations.

    • 4Ws of Problem Canvas (Problem Scoping): Who, What, Where, Why

    • Testing Dataset: The dataset used to assess the performance of a machine learning algorithm after training.

    • AI Modeling Approaches: Supervised, Unsupervised, Reinforcement Learning

    • Evaluation Stage Objective: To evaluate the prediction accuracy of the machine learning algorithm before deployment.

    • Artificial Neural Network Analogy: Parallel processing

    • Authentic Data Acquisition Sources: Sensors, Surveys, Web Scraping

    • Data Visualization for Continuous Data (e.g., Exam Scores): Linear graph

    • Neural Network Architecture: A mesh of multiple hidden layers/neurons

    • Classification AI Model: A model that categorizes data into predefined classes based on labeled data.

    • Regression AI Model: A model that predicts continuous values based on input data.

    • Clustering AI Model: An unsupervised learning algorithm that groups data points based on similarity.

    • Data Exploration Stage: Analyzing acquired data to verify correctness, ensure accuracy, and identify errors. Data must match specifications.

    • Artificial Neural Network Features: Mimics the human brain, automatically extracts features, useful for large datasets, fault-tolerant (can operate with partial data), and capable of parallel processing.

    • AI Project Cycle Importance: Provides a structured approach to Al project development.

    • Data Size & Model Performance (ANN): The performance of AI applications depends on the quality and quantity of data used for training. Large, representative datasets are preferred. Data must be relevant to the task.

    • 4Ws Problem Canvas Detail:

    • Who: Stakeholders directly or indirectly impacted.

    • What: Nature of the problem, what information is available.

    • Where: Location, context, situation where problem arises.

    • Why: Benefits for stakeholders and society.

    • Rule-Based vs. Learning-Based AI:

    • Rule-Based: Machine follows predefined rules provided by a developer.

    • Learning-Based: Machine learns patterns and relationships from data without explicit instructions.

    • Data Acquisition Ethics: Obtaining data ethically (with permission, transparency) is crucial for accurate and reliable AI projects.

    • Sustainable Development Goals (SDGs) Problems (Examples): Detailed problems for specific development goals are listed in the document.

    Studying That Suits You

    Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

    Quiz Team

    Related Documents

    CBSE Class 10 Artificial Intelligence Past Paper PDF

    Description

    Test your knowledge on the fundamentals of Artificial Intelligence through this question bank specifically designed for Class 10 students. Explore topics like AI project cycles, modeling approaches, and the sustainable development goals. Prepare effectively and gain a deeper understanding of how AI impacts our world.

    More Like This

    Use Quizgecko on...
    Browser
    Open
    Browser
    Browser