The solution harnesses historical customer data for segmentation, incorporating customer IDs and various features such as purchase frequency, credit limits, and the number of purchases. It formulates the clustering problem as an optimization problem and solves it using the D-Wave's hybrid solver....
Algorithm - Fulfilled on Amazon SageMaker
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The long-memory dynamic factor model (LMDFM) algorithm is to make (1) analysis of observed multiple (vector) time-series, (2) multi-step forecasts of multivariate (vector) time-series, and (3) multi-step forecasts of multivariate volatility (variance-covariance matrix) of vector time-series. The...
Algorithm - Fulfilled on Amazon SageMaker
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This algorithm performs time series clustering with an unsupervised convolutional neural network trained using contrastive learning followed by a K-Means clusterer. It implements both training and inference from CSV data and supports both CPU and GPU instances. The training and inference Docker...
Algorithm - Fulfilled on Amazon SageMaker
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