Which of the following packages is NOT associated with AutoML models?

TensorFlow is primarily a deep learning framework that is widely used for building neural networks and other advanced machine learning algorithms. While it can be leveraged in large-scale machine learning tasks, it does not specifically focus on automated machine learning (AutoML) processes. AutoML is concerned with automating the process of applying machine learning to real-world problems, which involves selecting models, feature engineering, and hyperparameter tuning without extensive manual intervention.

In contrast, the other mentioned packages—Scikit-learn, Prophet, and LightGBM—have components or functionalities that align more closely with AutoML practices. Scikit-learn provides numerous tools for preprocessing, model selection, and evaluation, which are critical in the AutoML workflow. Prophet offers forecasting capabilities that can be automated, especially in time series analysis. LightGBM is a gradient boosting framework that supports efficient model building and is often included in AutoML pipelines for tasks such as classification and regression.

Thus, TensorFlow does not fit within the context of typical AutoML model packages, making it the correct choice for this question.