MLOps with Ray: Best Practices and Strategies for Adopting Machine Learning Operations

© Hien Luu, Max Pumperla and Zhe Zhang 2024

H. Luu et al.MLOps with Rayhttps://doi.org/10.1007/979-8-8688-0376-5_4

4. Model Training Infrastructure

Hien Luu¹  , Max Pumperla² and Zhe Zhang³

(1)

Santa Clara, CA, USA

(2)

Bad Segeberg, Germany

(3)

Sunnyvale, CA, USA

 

In the ML development process, the phase that follows feature engineering is known as model training. This crucial phase involves selecting and deciding an ML algorithm from the pool of diverse options, and training it using the selected features. The objective is to train the ML algorithm to learn patterns within these features so it reasonably can make accurate predictions on new and unseen data. The model training pipeline encompasses several key steps: ML algorithm selection, model training, ...