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Motion is the number one cause for injuries in the workplace as well as the structural driver for athletic activities. Modjoul Motion model identifies 4 major activities and corresponding metrics. This model detects not only walking but also bends, twists and stationary activity. It accepts input...

Model Package - Fulfilled on Amazon SageMaker

  • Version 1.0
  • Sold by KNIME

Predicts the credit risk (good or bad) using the input data that captures information about a specific person. Provide the input data in JSON format. The model was trained using a generated dataset of credit information. The model is deployed using a KNIME workflow (www.knime.com).

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


Evaluate the similarity of two words, sentences, paragraphs, or documents. Get a score of how similar or different two text are. For an example of a real use case, this inference model was used in creating the first semantic keyword research tool that can sort by relevance. This inference model...

Model Package - Fulfilled on Amazon SageMaker

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  • Version 1
  • Sold by Peak

You can’t grow your business effectively if customers are leaving too often, and it’s important to know what can turn a good customer into a great one. However, for non-contractual business models - including most retailers - customer churn can be difficult to define, as customers aren't locked...

Algorithm - Fulfilled on Amazon SageMaker


This model classifies images of objects into trash or recyclable (cardboard, glass, paper, aluminum, or plastic) and returns a class probability for images of single objects. It was trained images taken on cell phone images of trash items submitted by Figure Eight contributors all over the world...

Model Package - Fulfilled on Amazon SageMaker


A high frequency of issues can generate an overwhelming number of tickets and incorrect delegation to teams to handle them. This leads to a spike in MTTR (mean time taken to resolve) and a dip in FCR (First Call Resolution). The solution mitigates these issues by training a multi-factor ML model...

Algorithm - Fulfilled on Amazon SageMaker


Train a BERT model from scratch on your own text corpus using the open-source FARM framework. This is helpful if you are working with another language or in a particular domain that uses a specific jargon, e.g. law, finance, biomed or engineering. Your input: A training corpus in a txt file and a...

Algorithm - Fulfilled on Amazon SageMaker

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Prosper Insights & Analytics' propensity model predicts the probability that a U.S. adult consumer uses Lyft. Based on a set of basic demographics, the model identifies individuals who are likely to use the ride share service. The model was trained with data from Prosper's large Media Behaviors &...

Model Package - Fulfilled on Amazon SageMaker

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Trained on Novetta’s hand-tagged data, this model classifies user-provided text into one of the following categories: Civilian Casualties; Freedom of the Press; Human Rights; Human Rights Investigations; Humanitarian Aid; Impact of Chemical, Biological, Radioactive, and Nuclear Weapons; Prisoners;...

Model Package - Fulfilled on Amazon SageMaker