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Using predictive modeling and machine learning techniques, CARE™ Disease Prediction analyzes more than 14 billion medical claims to identify early indicators of disease for local markets and disease onset across the United States. These predictions give you the information you need to plan outreach...

Model Package - Fulfilled on Amazon SageMaker

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This SageMaker model package provides a REST api to analyze the sentiment of English sentences. The API accepts input as JSON, CSV or plain text, and identifies the sentiment (positive or negative) and provides a confidence level (float number from 0 to 1). We welcome your feedback at...

Model Package - Fulfilled on Amazon SageMaker


Effective scheduling for hospital admission is a major challenge as there is uncertainty in patient’s length of stay and large errors in estimations can lead to capacity pressures. To tackle this, Virtusa-Xlabs has developed a Deep Learning based solution which will accurately predict how long a...

Model Package - Fulfilled on Amazon SageMaker

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Using predictive modeling and machine learning techniques, CARE™ Disease Prediction analyzes more than 14 billion medical claims to identify early indicators of disease for local markets and disease onset across the United States. These predictions give you the information you need to plan outreach...

Model Package - Fulfilled on Amazon SageMaker

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Image Embeddings using Singular Value Decomposition (SVD) can be used for semantic search, dimensionality reduction, and anomaly detection. Given a batch of images, singular values and vectors are computed using this algorithm.

Algorithm - Fulfilled on Amazon SageMaker


Prosper Insights & Analytics' propensity model predicts the probability that a U.S. adult consumer shops at a specific retailer. Based on a set of basic demographics, the model identifies individuals who are likely to shop at that retailer. The model was trained with data from Prosper's large...

Model Package - Fulfilled on Amazon SageMaker

  • Version 1.0
  • Sold by KNIME

Predicts the sentiment of forum reviews. Provide the text in JSON format. The model was trained using an open dataset of airline reviews. The model is deployed using a KNIME workflow (www.knime.com).

Model Package - Fulfilled on Amazon SageMaker


The MTTR (Mean Time to Resolution) predictor is an AI/ML based solution which predicts the time taken by a service agent to solve a specific ticket or an incident request. The solution learns the efficiency, experience and workload management metrics for various ticket types solved by service...

Model Package - Fulfilled on Amazon SageMaker

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  • Version 20.01
  • Sold by CVEDIA

Detect a variety of bicycles, standing scooters, and riders with the CVEDIA POROS Scooter and Bicycle Detector. Trained extensively using standing scooters, tandem bikes, quad bikes, and tricycles, POROS is also able to detect common detection issues such as groups of bicycles and partial...

Model Package - Fulfilled on Amazon SageMaker


Autocode Text To PHP Code Recommender takes a code related user text query as input and returns 3 optimal PHP code recommendations from Github that will be syntactically and semantically correct. Considering the ever increasing number of programming languages and the frameworks that are built...

Model Package - Fulfilled on Amazon SageMaker