Podcast
Questions and Answers
Scalability is a characteristic of Cloud computing.
Scalability is a characteristic of Cloud computing.
True (A)
Private Deployment Model is managed by the provider.
Private Deployment Model is managed by the provider.
False (B)
Machine Learning is a subfield of Artificial Intelligence.
Machine Learning is a subfield of Artificial Intelligence.
True (A)
Reinforcement Learning is a type of Supervised Learning.
Reinforcement Learning is a type of Supervised Learning.
Deep Learning is a subfield of Machine Learning.
Deep Learning is a subfield of Machine Learning.
SLA stands for Service Level Agreements.
SLA stands for Service Level Agreements.
Unsupervised Learning is used for Classification tasks.
Unsupervised Learning is used for Classification tasks.
Machine Learning is widely used in gaming, robotics, and industrial automation.
Machine Learning is widely used in gaming, robotics, and industrial automation.
In Cloud computing, the Pay-per-usage model is a benefit of scalability.
In Cloud computing, the Pay-per-usage model is a benefit of scalability.
Machine Learning can only be applied to data that is already labeled.
Machine Learning can only be applied to data that is already labeled.
Deep Learning is a type of Reinforcement Learning.
Deep Learning is a type of Reinforcement Learning.
In Cloud computing, the Public Deployment Model is managed by the provider.
In Cloud computing, the Public Deployment Model is managed by the provider.
Artificial Intelligence is a subfield of Machine Learning.
Artificial Intelligence is a subfield of Machine Learning.
In Machine Learning, Supervised Learning is used for Clustering tasks.
In Machine Learning, Supervised Learning is used for Clustering tasks.
Cloud computing provides Flexible resource allocation through self-service on demand.
Cloud computing provides Flexible resource allocation through self-service on demand.
Machine Learning is a type of Artificial Intelligence that can mimic human behavior.
Machine Learning is a type of Artificial Intelligence that can mimic human behavior.
In Cloud computing, the Hybrid Deployment Model combines Public and Private clouds.
In Cloud computing, the Hybrid Deployment Model combines Public and Private clouds.
Unsupervised Learning is used for Regression tasks.
Unsupervised Learning is used for Regression tasks.
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Study Notes
Cloud Computing
- Flexible self-service, network-accessible computing resource pools that can be allocated to meet demand.
- Service models: IaaS, PaaS, SaaS.
- Deployment models: Private, Public, Hybrid.
- Benefits:
- Scalability
- Storage
- Security
- Data-loss prevention
- Maintenance
- Pay-per-usage of resources
- Accessibility
- Managed by the provider
- Flexible resource assignment
- Characteristics:
- Network accessible
- Sustainable
- Managed through self-service on demand
- SLA: Service Level Agreements
Machine Learning
- Definition: Process used to achieve artificial intelligence, involving designing algorithms that can learn from data to become more accurate and effective over time.
- Categories:
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Supervision:
- Classification: yes or no
- Regression: continuous
- Clustering: un-supervised
- Reinforcement learning:
- Training itself using trial and error
- Models learn from external interactions and improve with time
- Applications:
- Widely used in gaming, robotics, and industrial automation
- Healthcare and online stock trading
- Deep learning is a subfield of machine learning, inspired by how the brain works
Cloud Computing
- Flexible self-service, network-accessible computing resource pools that can be allocated to meet demand.
- Service models: IaaS, PaaS, SaaS.
- Deployment models: Private, Public, Hybrid.
- Benefits:
- Scalability
- Storage
- Security
- Data-loss prevention
- Maintenance
- Pay-per-usage of resources
- Accessibility
- Managed by the provider
- Flexible resource assignment
- Characteristics:
- Network accessible
- Sustainable
- Managed through self-service on demand
- SLA: Service Level Agreements
Machine Learning
- Definition: Process used to achieve artificial intelligence, involving designing algorithms that can learn from data to become more accurate and effective over time.
- Categories:
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Supervision:
- Classification: yes or no
- Regression: continuous
- Clustering: un-supervised
- Reinforcement learning:
- Training itself using trial and error
- Models learn from external interactions and improve with time
- Applications:
- Widely used in gaming, robotics, and industrial automation
- Healthcare and online stock trading
- Deep learning is a subfield of machine learning, inspired by how the brain works
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