Cloud Database Cost Forecasting generates 24 hours of forward forecast of database cost using historical data. This solution will help businesses to better optimize their on-cloud hosted database resources and foresee their cost fluctuations. It uses ensemble ML algorithms with automatic model...
Model Package - Fulfilled on Amazon SageMaker
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The variational Bayesian filtering factor analysis (VBfFA) algorithm/model is a filter with dimension-reduction, or rank-reduction, to extract a number of ever-evolving unobserved common factors, or signals from common sources, underlying and influencing a large number of related...
Algorithm - Fulfilled on Amazon SageMaker
Energy Consumption Forecasting generates 30 months of forward forecast of the consumption using historical data. It uses ensemble ML algorithms with automatic model selection algorithms. This solution provides consistent and better results due to its ensemble learning approach. This solution...
Model Package - Fulfilled on Amazon SageMaker
The application of Machine Learning Technology offers the possibility of using predictive algorithms that provide greater precision than the traditional statistical methods. Based on advanced analytics and statistical models that are trained automatically and continuously through the input of new...
Mphasis time series ticket forecasting helps businesses predict the number of tickets of a specific type based on historic data. This will help businesses assess the level of automation as well as human intervention required to resolve the issues and plan accordingly. It uses ensemble ML algorithms...
Model Package - Fulfilled on Amazon SageMaker
Data evolves over time, causing a change in the distributions and interpretation of data and a corresponding degradation in model performance. The Drift Detector uses an incremental learning method, in which each incoming instance retrains the model. The solution detects drifts in the model output,...
Model Package - Fulfilled on Amazon SageMaker
Cloud Network Cost Forecasting generates 24 hours forward forecast of network cost using historical data. This solution will help businesses to better optimize their on-cloud network infrastructure and foresee their cost fluctuations. It uses ensemble ML algorithms with automatic model selection...
Model Package - Fulfilled on Amazon SageMaker
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The Yule-Walker-PCA Autoregressive Model (YWpcAR) algorithm is developed to simultaneously analyze and forecast many time-series individually, assuming each time-series is influenced by evolution of "hidden components" (resulted from PCA). Here PCA standards for "principal components analysis"....
Algorithm - Fulfilled on Amazon SageMaker
Cloud compute cost forecasting helps businesses assess the cost incurred from their cloud compute resource based on historic data. This will help businesses get an understanding of the potential cost for their VM instances, clusters, snapshots, etc. to help them better plan their compute resources....
Model Package - Fulfilled on Amazon SageMaker
InfraGraf Bandwidth Usage Forecasting helps businesses assess their network usage based on historic data. This will help to manage network requirements and make cost-efficient decisions. It uses ensemble ML algorithms with automatic model selection algorithms. This solution provides consistent and...
Model Package - Fulfilled on Amazon SageMaker
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