1. What Is MLOps MLOps is short for Machine Learning Operations, and it describes the standardization and engineering of the entire lifecycle around model development. MLOps includes the following key steps: Data management: storing, accessing, cleaning, and transforming data Model development: algorithm development and model construction Model training and tuning: training models on data, adjusting hyperparameters to optimize the model, and fine-tuning models Model evaluation: testing a model’s accuracy, generalization ability, and performance metrics Model deployment: deploying the model to the target environment and converting the model Model monitoring: monitoring the model’s behavior, performance degradation, data drift, and robustness Another similar concept is ModelOps.

1. Keywords Machine Learning (ML) The technology of automatically acquiring knowledge from data. Neural Network (NN) A model that imitates the structure and learning mechanism of biological neural networks; one of the branches of machine learning. The structure of a neural network consists of an input layer, hidden layers, and an output layer.

1. Introduction Jupyter Notebook (formerly IPython notebook) is an interactive notebook that supports running more than 40 programming languages. Jupyter Notebook is in fact a web application that lets you create and share program documents, with support for live code, mathematical equations, visualizations, and Markdown. Its uses include data cleaning