Machine Learning Platforms

Question 1

What do machine learning platforms do?

Answer 1

Machine learning platforms facilitate machine learning from end to end, giving users the ability to manage the entire data lifecycle, from data ingestion to inference.

Question 2

What is data ingestion?

Answer 2

Providing users the ability to integrate and ingest data from various internal and external sources, including enterprise applications, databases, and internet of things (IoT) devices

Question 3

What is data preparation?

Answer 3

Data cleansing and data augmentation

Question 4

What is feature engineering?

Answer 4

Transforming raw data into features that better present the underlying problem to the predictive models

Question 5

What is model training?

Answer 5

Proper values are determined for various weights and biases from the data either by supervised or unsupervised learning

Question 6

What is model deployment?

Answer 6

Making the model available in production environments where they provide their predictions to other systems

Question 7

What is model comparison?

Answer 7

Gives the user the ability to compare models to a baseline or previous result to determine the quality of the model built. Also, monitoring metrics like accuracy and loss

Question 8

What are examples of familiar frameworks a platform might have support for?

Answer 8

ONNX, Python, PyTorch, scikit-learn or TensorFlow

Question 9

What protections would a platform have?

Answer 9

Enterprise-grade governance, security, and control