We present a lightweight system to extract, store and manage metadata and provenance
information of common artifacts in machine learning (ML) experiments: datasets, models …

Time series forecasting, that predicts events through a sequence of time, has received
increasing attention in past decades. The diverse range of time series forecasting models …

Large-scale data analytics using machine learning (ML) underpins many modern data-
driven applications. ML systems provide means of specifying and executing these ML …

As data-driven methods are becoming pervasive in a wide variety of disciplines, there is an
urgent need to develop scalable and sustainable tools to simplify the process of data …

Abstract Machine learning (ML) models have been quite successful in predicting outcomes
in many applications. However, in some cases, domain experts might have a judgment …

Data gathered from various devices have to be observed by human operators manually for
extended durations which is not viable and may lead to imprecise results. Data are analyzed …

Despite all of the power that machine learning and artificial intelligence (AI) models bring to
applications, much of AI development is currently a fairly ad hoc process. Software …