Cloud Computing Fundamentals
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Questions and Answers

What is the primary goal of machine learning?

  • To mimic human intelligence
  • To process large amounts of data
  • To achieve artificial intelligence (correct)
  • To design algorithms
  • What is a characteristic of cloud computing?

  • Limited resource allocation
  • Managed by the user
  • Network accessible (correct)
  • Fixed storage capacity
  • What is a type of machine learning?

  • Cloud computing
  • Artificial intelligence
  • Reinforcement learning (correct)
  • Deep learning
  • What is the primary goal of supervised learning?

    <p>To classify data</p> Signup and view all the answers

    What is a benefit of cloud computing?

    <p>Pay-per-usage of the resources</p> Signup and view all the answers

    What is a characteristic of private cloud deployment?

    <p>Private and secure</p> Signup and view all the answers

    What is the primary goal of reinforcement learning?

    <p>To train models using trial and error</p> Signup and view all the answers

    What is a benefit of using cloud computing resources?

    <p>Flexible resource allocation</p> Signup and view all the answers

    Study Notes

    Cloud Computing

    • Cloud computing provides flexible self-service, network-accessible computing resource pools that can be allocated to meet demand.
    • There are three service models: IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service).
    • Deployment models include Private, Public, and Hybrid.
    • Benefits of cloud computing include scalability, storage, security, data-loss prevention, maintenance, and pay-per-usage of resources.
    • Characteristics of cloud computing include network accessibility, sustainability, and self-service on-demand allocation of resources.
    • Service Level Agreements (SLA) are used to define the quality of service.

    Machine Learning (ML)

    • Artificial Intelligence (AI) is the ability to mimic human intelligence and behavior.
    • Machine Learning (ML) is the process of achieving AI through designing algorithms that learn from data to become more accurate and effective over time.
    • ML subfields include Deep Learning, which draws inspiration from how the brain works.
    • Categories of ML include Supervised Learning, Unsupervised Learning, and Reinforcement Learning.
    • Supervision types include Classification (yes/no), Regression (continuous), Clustering, and Unsupervised Learning.
    • Reinforcement Learning involves training using trial and error, with models learning from external interactions and improving with time.
    • Applications of ML include gaming, robotics, industrial automation, healthcare, and online stock trading.

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    Description

    Learn the basics of cloud computing, including its definition, service models, deployment models, benefits, and key features.

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