Cloud-native services for machine learning refer to platforms and tools designed to leverage cloud computing’s scalability, flexibility, and efficiency for developing, training, and deploying machine learning models. These services enable data scientists and engineers to build models using various frameworks and languages while managing resources dynamically. By utilizing cloud infrastructure, users can access powerful computing resources, such as GPUs and TPUs, and benefit from integrated tools for data storage, model management, and deployment. This approach simplifies the machine learning lifecycle, allowing teams to focus on innovation rather than infrastructure management.