Machine learning (ML) and artificial intelligence (AI) have transitioned from exclusive fields to accessible technologies through services like Amazon ML, which simplifies the integration of ML models into applications by offering ready-made models and infrastructure for training and deployment. While ML techniques are broadly categorized into supervised and unsupervised learning, Amazon ML focuses on commonly used supervised models like binary and multiclass classification, as well as linear regression, making it easier for developers to implement basic predictive functionalities without the need for extensive setup. The service allows users to upload data, select models, and deploy them with API endpoints, streamlining the process and reducing the technical burden typically associated with ML development. However, while Amazon ML is effective for basic models, it may fall short for more advanced applications, such as those requiring deep learning, for which Amazon AI provides additional support and infrastructure.