Machine Learning Engineering for Edge AI: Challenges and Best Practices

Machine learning engineering is the field of developing, implementing, and maintaining machine learning systems. It involves the application of engineering principles to the design, development, and deployment of machine learning models, algorithms, and applications. The primary focus of ML engineering is to build scalable and efficient machine learning systems that can process large volumes of data and generate accurate predictions. It involves various tasks such as data preparation, model development, model training, model deployment, and model monitoring. ML engineering requires a combination of skills in computer science, mathematics, statistics, and domain-specific knowledge.