… to manage machine learning models. ModelDB automatically tracks machine learning models
in … them intelligently, and allows flexible exploration of models via SQL as well as a visual …

… experience in predictive and machine learning models and working with distributed systems.
Academic and/or practical background in Machine Learning are particularly relevant for this …

… to make predictions and draw inferences, suggesting that scientists are opting for models …
a machine learning model? Or are the assumptions behind why minimal models provide …

… In this study, we describe an alternative methodology for applying machine learning, in …
corresponding custom machine learning code is then generated automatically. This model-based …

… This paper presents an overview of machine learning models used in flood prediction, and
… at least two machine learning models were compared. To do so, the prediction models were …

… machine learning model is trained to perform inference and make a diagnostic call. Unlike
the traditional locked model, the current state AI model … state AI model, the model provides the …

… For our purposes, a machine learning pipeline consists of several steps shown in Figure 1.
… 5.1 Abusing Model Capacity We exploit the fact that modern machine learning models have …

… end users, except machine learning experts, can hardly produce strong models. … machine
learning model with a specification which explains the purpose and/or specialty of the model. …

… provides a hybrid machine learning model for predicting CKD as an example towards
improving the healthcare services. The proposed VMs optimization model is implemented using …

… machine learning to noise, a good model cannot substitute for bad data, keeping in mind that
models … it has been stated that “All models are wrong; some models are useful (George Box)…