What ML pipelines are

Undoubtedly, in recent years, the field of ML has witnessed remarkable advancements, revolutionizing industries and empowering innovative applications. As the demand for more sophisticated and accurate models grows, so does the complexity of developing and deploying them effectively. The industrial introduction of ML systems called for more rigorous testing and validation of these ML-based systems. In response to these challenges, the concept of ML pipelines has emerged as a crucial framework to streamline the entire ML development process, from data preprocessing and feature engineering to model training and deployment. This chapter explores the applications of MLOps in the context of both cutting-edge deep learning (DL) models such as Generative Pre-trained Transformer (GPT) and traditional classical ML models.

We begin by exploring the underlying concepts of ML pipelines, stressing their importance in organizing the ML workflow and promoting collaboration...