MCQs

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Overall MCQs for Reference

What is a primary benefit of using a shared drive for machine learning collaboration?
a. Higher computational power
b. Centralized storage accessible by team members
c. Automatic model tuning
d. Real-time data stream integration
Answer: b. Centralized storage accessible by team membersgoogle+1
In the context of shared drives, who owns the content stored within?
a. The individual user who uploaded the file
b. The project manager only
c. The entire team or organization
d. Third-party vendors
Answer: c. The entire team or organizationithelp.brown+1
Which of the following increases productivity when using shared drives in machine learning projects?
a. Decentralized artifact storage
b. Manual file transfer
c. Organized folder structure
d. Hardcoded access paths
Answer: c. Organized folder structureofficiency+1
How do shared drives help with version control?
a. They automatically delete old files
b. They provide clear guidelines and reduce file duplication
c. They encrypt files automatically
d. They block all outside access
Answer: b. They provide clear guidelines and reduce file duplicationofficiency
What is a significant risk of using shared drives for sensitive machine learning data?
a. Increased computational latency
b. Data leakage due to excessive sharing permissions
c. File format incompatibility
d. Loss of network connectivity
Answer: b. Data leakage due to excessive sharing permissionsgca.isa+1
Which shared drive feature supports large-scale machine learning deployments?
a. Individual file encryption only
b. Read-only attachment to thousands of compute nodes
c. Limited access to a single user
d. Real-time code execution
Answer: b. Read-only attachment to thousands of compute nodescloud.google
The main difference between a shared drive and “My Drive” in Google Workspace is:
a. “My Drive” is shareable with everyone by default
b. Shared drives are team-owned, while “My Drive” is individually owned
c. Shared drives cannot store machine learning models
d. “My Drive” always has administrator access rights
Answer: b. Shared drives are team-owned, while “My Drive” is individually ownedgoogle+1
What protocol supports open and secure data sharing for interoperability in machine learning projects?
a. FTP
b. Delta Sharing
c. Telnet
d. SFTP
Answer: b. Delta Sharinglearn.microsoft
Shared drives in cloud-based ML enable what key collaboration benefit?
a. Exclusive write permissions
b. Streamlined sharing with external collaborators
c. No user access management
d. Clock synchronization
Answer: b. Streamlined sharing with external collaboratorspremiercloud+1
To manage access at scale, it is best practice to:
a. Add each user individually
b. Use group-based permissions
c. Allow anonymous access
d. Grant only view permissions
Answer: b. Use group-based permissionsithelp.brown
What type of files can be stored in a shared drive for ML projects?
a. Only code scripts
b. Only structured databases
c. Any file type (datasets, code, documentation, models)
d. Only PDFs
Answer: c. Any file type (datasets, code, documentation, models)workspace.google+1
Which security practice is recommended for sharing ML data on a shared drive?
a. Disable all logging features
b. Encrypt data during transmission and storage
c. Use default settings only
d. Allow unrestricted edit access
Answer: b. Encrypt data during transmission and storagegca.isa
Shared drives simplify ML model deployment by:
a. Making only one model accessible at a time
b. Enabling simultaneous read access by multiple nodes
c. Preventing any file editing
d. Disallowing remote access
Answer: b. Enabling simultaneous read access by multiple nodeslearn.microsoft+1
What organizational structure enables flexible access while keeping sensitive ML data secure?
a. Single-folder structure
b. Open-access flat structure
c. Hybrid structure with restricted departmental and open drives
d. Fully public repository
Answer: c. Hybrid structure with restricted departmental and open drivesgatlabs
Which of the following is a potential pitfall of poorly managed shared drives in ML contexts?
a. Drive sprawl and confusion around access rights
b. Automatic drive cleanup
c. On-the-fly user verification
d. Serverless data storage
Answer: a. Drive sprawl and confusion around access rightsgoogle+1
When using Google Shared Drives, what happens to user access when someone leaves the organization?
a. Files are deleted
b. Their inherited group access continues
c. All permissions are revoked immediately
d. Only admins retain access
Answer: b. Their inherited group access continuesithelp.brown
Why are distributed file systems often preferred over local storage for big ML projects?
a. They provide less data redundancy
b. They are less scalable
c. They offer high scalability and fault tolerance
d. They eliminate the need for any team collaboration
Answer: c. They offer high scalability and fault toleranceeducative+1
What is a primary organizational benefit of shared drives?
a. Decentralized auditing
b. Improved accessibility of data
c. Reducing the number of users
d. Bypassing enterprise policies
Answer: b. Improved accessibility of datagoogle+1
For compliance in ML projects, monitoring shared drive activity helps:
a. Hide all user actions
b. Ensure security and prevent unauthorized downloads
c. Speed up training automatically
d. Disable all notifications
Answer: b. Ensure security and prevent unauthorized downloadsgatlabs
Shared drives can be used in ML for:
a. Storing only intermediate outputs
b. Centralizing documentation and tracking experiments
c. Real-time distributed GPU rendering
d. Minimizing traceability
Answer: b. Centralizing documentation and tracking experimentspremiercloud+1
Periodic review of shared drive permissions is important because:
a. Drives may vanish without warning
b. Group membership and team needs change over time
c. Backup utilities run only at midnight
d. Drives are publicly listed
Answer: b. Group membership and team needs change over timeithelp.brown
What is a performance benefit of shared encoder models with shared storage in ML?
a. Increased latency
b. Significant memory and storage efficiency
c. Lossy compression of training data
d. Limited scalability
Answer: b. Significant memory and storage efficiencydzone
Which element is NOT an advantage of distributed file storage for ML model artifacts?
a. Self-healing after node failures
b. Transparent access for users
c. Only local node access
d. Replication for data protection
Answer: c. Only local node accesssystemdesignhandbook
Secure multi-party computation is used in shared drive contexts to:
a. Speed up network transmission
b. Ensure data remains private during collaborative computation
c. Maximize file duplication
d. Prevent file versioning
Answer: b. Ensure data remains private during collaborative computationgca.isa
Which best practice should be followed to avoid duplicate shared drives?
a. Allow each team member to create new drives at will
b. Coordinate drive creation and use unique folder names
c. Disable all sharing features
d. Limit drive size arbitrarily
Answer: b. Coordinate drive creation and use unique folder namesgoogle+1
What access control method helps automate changes when team members join or leave a project in shared drives?
a. Direct user assignment only
b. External guest accounts
c. Linking access to managed groups (like Google Groups)
d. IP whitelist only
Answer: c. Linking access to managed groups (like Google Groups)ithelp.brown
A limitation of shared drives is:
a. Inability to share whole folders with non-members
b. Support only for binary files
c. Exclusive use for analytics workloads
d. Guaranteed infinite storage
Answer: a. Inability to share whole folders with non-membersithelp.brown
Which type of drive organization is suitable for company-wide ML policy sharing?
a. Departmental Drive
b. View-Only Shared Drive
c. Open Shared Drive
d. None of the above
Answer: b. View-Only Shared Drivegatlabs
When organizing experiments and datasets, a shared drive provides:
a. Fragmented storage and difficult access control
b. Central reference point and version clarity
c. Randomized storage patterns
d. No audit trail
Answer: b. Central reference point and version clarityofficiency
A scalable shared storage infrastructure in ML often uses:
a. Removable flash drives
b. Distributed file systems like HDFS or Google File System
c. Static HTML pages
d. Email attachments
Answer: b. Distributed file systems like HDFS or Google File Systemeducative+1
Shared drives and open sharing in ML can cause what privacy concern?
a. Overly restrictive data access
b. Data exfiltration by unauthorized users
c. Reduced storage costs only
d. Complete device isolation
Answer: b. Data exfiltration by unauthorized usersarxiv+1
The READ_ONLY_MANY feature in cloud storage means:
a. Data can be written by only one user at a time
b. One storage volume is accessible as read-only by multiple compute instances
c. Storage is deleted after each use
d. Data is encrypted locally only
Answer: b. One storage volume is accessible as read-only by multiple compute instancescloud.google
Delta Sharing enables what in ML infrastructure?
a. Proprietary protocol lock-in
b. Open, cross-platform data sharing
c. Anonymous access by default
d. Limited file support
Answer: b. Open, cross-platform data sharinglearn.microsoft
In shared drive systems, robust monitoring helps ensure:
a. Fast data deletion
b. Compliance with security and governance requirements
c. Unrestricted access for all users
d. All models automatically re-trained
Answer: b. Compliance with security and governance requirementslearn.microsoft+1
What is a recommended tip to reduce drive sprawl in cloud shared drives?
a. Disable users’ ability to create Shared Drives unnecessarily
b. Allow all employees to create drives without restriction
c. Use a single drive for all projects
d. Archive shared drives weekly
Answer: a. Disable users’ ability to create Shared Drives unnecessarilygatlabs
Redundancy in distributed shared drives provides:
a. More risk of data loss
b. Increased data availability and fault tolerance
c. Slower file access
d. Limited scalability
Answer: b. Increased data availability and fault tolerancesystemdesignhandbook+1
Shared drives in ML are NOT ideal for:
a. Centralizing collaborative work
b. Tracking changes in group projects
c. Isolating all data to single-user folders
d. Securely sharing data with access controls
Answer: c. Isolating all data to single-user folderspremiercloud+1
Effective use of shared drives relies on:
a. Manual email notification for every change
b. Consistent naming and documentation practices
c. Locking all users out during work hours
d. Random project structures
Answer: b. Consistent naming and documentation practicesofficiency+1
Why is periodic security assessment necessary for shared drives in ML?
a. To ensure only ML engineers can access data
b. To identify vulnerabilities in shared tools and permissions
c. For automatic hyperparameter tuning
d. For daily snapshots
Answer: b. To identify vulnerabilities in shared tools and permissionsgca.isa
Centralizing ML assets on a shared drive aids with:
a. Siloing teams
b. Reproducibility and consistent workflows
c. Reducing data access speed
d. Forcing local backups only
Answer: b. Reproducibility and consistent workflowspremiercloud+1
In cross-team ML projects, shared drives allow for:
a. Fragmented datasets
b. Team-specific ownership and universal access
c. No access from outside the local network
d. Proprietary format requirement
Answer: b. Team-specific ownership and universal accessworkspace.google+1
Using a hybrid drive structure for ML teams is best for:
a. Projects requiring granular control and secure sharing
b. Projects with static, universal access needs
c. Teams without any remote members
d. Projects with no collaboration
Answer: a. Projects requiring granular control and secure sharinggatlabs
Which of the following is NOT a recommended shared drive practice?
a. Consistent access review
b. Team-named folders
c. Sharing folders with personal emails
d. Collaboration policy documentation
Answer: c. Sharing folders with personal emailsgoogle+1
In distributed ML serving, what does decoupling storage from model code achieve?
a. Code redundancy
b. Optimized resource allocation and scalable deployment
c. Reduced auditability
d. Increased latency
Answer: b. Optimized resource allocation and scalable deploymentdzone+1
What drives collaboration in shared ML model development?
a. Local hardware limitations
b. Shared drive’s centralized access and common data pool
c. Decentralized communication only
d. Siloed datasets
Answer: b. Shared drive’s centralized access and common data poolgoogle+1
Which is a feature of Azure shared disks for ML clusters?
a. Can only be mounted by one VM at once
b. Allows multiple VMs to attach a disk simultaneously
c. Deletes old snapshots daily
d. Enforces instant write lock
Answer: b. Allows multiple VMs to attach a disk simultaneouslylearn.microsoft
Secure sharing practices in ML include:
a. Using clear governance and monitoring policies
b. Disabling all permissions by default
c. Using obsolete storage protocols
d. Ignoring data lifecycle
Answer: a. Using clear governance and monitoring policieslearn.microsoft+1
What happens to files not owned by a user when trying to move them to a Google Shared Drive?
a. Moved without restrictions
b. Only files you own can be moved
c. All files are auto-encrypted
d. They are lost
Answer: b. Only files you own can be movedithelp.brown
Shared drives facilitate ML project continuity by:
a. Deleting inactive files after 24 hours
b. Preserving project artifacts and documentation for all team members
c. Restricting files to creators
d. Locking drives during weekends
Answer: b. Preserving project artifacts and documentation for all team membersgoogle+1
Which of the following must be periodically updated to ensure ML data governance in shared drives?
a. Individual folder owners
b. Shared drive access permissions and group memberships
c. Source code for every user
d. Local server backup policies
Answer: b. Shared drive access permissions and group membershipsgoogle+1

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