NCA-AIIO Question 47
Select 4An organization is setting up an AI development and deployment pipeline. They want to ensure proper lifecycle management for their models, from training to deployment and monitoring. Which of the following software components are crucial for achieving this goal?
- A
Model training frameworks such as TensorFlow or PyTorch
- B
Model versioning and registry systems like NVIDIA NGC or MLflow
- C
Monitoring and logging tools such as Prometheus or Grafana
- D
Data visualization platforms like Tableau
- E
Continuous integration/continuous deployment (CI/CD) tools like Jenkins or GitLab CI
Show answer and explanation
Correct answers: A, B, C, E
Explanation
The lifecycle of AI development and deployment involves multiple stages, including training, versioning, deployment, and monitoring. Software components like model training frameworks, versioning systems, monitoring tools, and CI/CD pipelines are all necessary to ensure smooth transitions between these stages. Data visualization tools like Tableau, while valuable for analytics, are not central to managing the AI lifecycle.
- A. Correct.
Model training frameworks like TensorFlow or PyTorch are essential for training AI models. They are a foundational part of the AI lifecycle.
- B. Correct.
Model versioning and registry systems help manage and track different versions of AI models, ensuring reproducibility and proper deployment processes.
- C. Correct.
Monitoring and logging tools allow teams to track the performance of AI models in production, detect anomalies, and ensure reliability.
- D. Incorrect.
While data visualization tools like Tableau are useful for presenting insights, they are not directly tied to the lifecycle management of AI development and deployment.
- E. Correct.
CI/CD tools such as Jenkins or GitLab CI are critical for automating the deployment of AI models and ensuring they are updated seamlessly in production.