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This algorithm performs time series forecasting with the Closed-Form Continuous-Depth (CfC) network. It implements both training and inference from CSV data and supports both CPU and GPU instances. The training and inference Docker images were built by extending the PyTorch 2.1.0 Python 3.10...
Algorithm - Fulfilled on Amazon SageMaker
This is a demo product from Amazon that showcases the Marketplace experience. It was created using this sample notebook https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.ipynb. Decision Trees (DTs) are a...
Model Package - Fulfilled on Amazon SageMaker
This post-pandemic Propensity Model determines the probability that a US adult does Fantasy Sports Regularly. Lift over Random 2.93. This post-pandemic Propensity model is one of a series of consumer classification models based on data from over 17,000 US adults surveyed in 2021 from Prosper's US...
Model Package - Fulfilled on Amazon SageMaker
This post-pandemic Propensity Model determines the probability that a US adult uses CBD for Skincare. Lift over Random 2.36. This post-pandemic Propensity model is one of a series of consumer classification models based on data from over 17,000 US adults surveyed in 2021 from Prosper's US Media...
Model Package - Fulfilled on Amazon SageMaker
This post-pandemic Propensity Model determines the probability that a US adult uses the Shop Now feature on Pinterest Regularly. Lift over Random 2.23. This post-pandemic Propensity model is one of a series of consumer classification models based on data from over 17,000 US adults surveyed in 2021...
Model Package - Fulfilled on Amazon SageMaker
Prosper Insights & Analytics' Fashion Conscious propensity model predicts the probability that a U.S. adult consumer is fashion conscious. Based on a set of basic demographics, the model identifies individuals for whom the newest fashion trends and styles are important. The model was trained with...
Model Package - Fulfilled on Amazon SageMaker
Data evolves over time, causing a change in the distributions and interpretation. This is known as drift and causes a degradation in ML model performance. The Drift Detector detects changes in the incoming data, and provides useful insights to the user with respect to the data and model behavior....
Model Package - Fulfilled on Amazon SageMaker
This solution takes a deep learning-based approach to learn and understand the patterns in Temperature sensor data. It aims at learning the normal behavior patterns of the sensor data during training process using generative algorithms. Once trained, the model can monitor and identify abnormal...
Algorithm - Fulfilled on Amazon SageMaker
Mphasis server storage forecasting helps businesses assess the storage space on their servers based on historic data. This will help businesses get an understanding of their server usage and help them plan better. It uses ensemble ML algorithms with automatic model selection algorithms. This...
Model Package - Fulfilled on Amazon SageMaker
Prosper Insights & Analytics' propensity model predicts the probability that a China adult consumer enjoys a specific leisure time activity. Based on a set of basic demographics, the model identifies individuals who are likely to participate in the activity. The model was trained with data from...
Model Package - Fulfilled on Amazon SageMaker
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