Data Science Model Deployments and Cloud Computing on GCP - Introduction-Vertex AI

Data Science Model Deployments and Cloud Computing on GCP - Introduction-Vertex AI

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

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This video provides an overview of Vertex AI, a managed machine learning platform on Google Cloud. It covers the entire machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment. Vertex AI supports both UI and code-based deployments and integrates with Jupyter Notebooks. It supports major frameworks like TensorFlow and PyTorch. The video also covers interactive model development, containerization, and deployment using Python SDK and UI. It introduces Kubeflow Pipelines for orchestration and focuses on Scikit-learn for custom model deployments.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is Vertex AI and what are its primary functions?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the end-to-end life cycle of a typical machine learning model as covered in the video.

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What machine learning frameworks are supported in Vertex AI?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain the process of interactive model development using Jupiter Notebooks in Vertex AI.

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What is Cube Flow and how does it relate to Vertex AI?

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