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WorksheetsPA Lab2 - PGPM -Quiz1
Total questions: 9
Worksheet time: 5mins
What is one way to update a deployed ML model on Render?
Retrain the model and redeploy with the updated files
Edit the model directly in the cloud
Use Render’s automatic retraining feature
Train the model with a larger dataset on Render
What is one common challenge when deploying ML models on the cloud?
Lack of computational power
Overfitting to training data
Ensuring low response time (l) for real-time predictions
Lack of labeled data
Which file format is often used to save a trained ML model for deployment?
.csv
.py
.pkl or .h5
.html
How is an ML model typically deployed as a service on Render?
By embedding it in a mobile application
By creating a API (app) or GraphQL API
By integrating it with a CRM system
By uploading it to a web browser
What is the typical cost structure for using Render platform? (apart from the limited free version)
Flat monthly fee
Pay-as-you-go, based on resources used
One-time payment
Free for unlimited usage
What is required to deploy a model API on Render?
A trained ML model and a web framework like Flask or FastAPI
Only the raw data used for training
A Render mobile application
Pre-installed cloud GPUs
Which programming languages are most commonly used to deploy ML models on Render?
Python and JavaScript
C++ and Ruby
HTML and CSS
SQL and NoSQL
What is the primary purpose of deploying an ML model?
To collect data
To make predictions or decisions in real-world scenarios
To train the model on new data
To store data securely
What is the "odd thing" here in relation to cloud deployment
Azure
AWS
GCP
Keras
