Given an input image, this will return object coordinates and category predictions. The format of coordinates is encoded as (left, top, right, bottom) of the absolute pixel locations. This model is trained on COCO dataset with 80 common object categories. It can be used as fast and reliable general...
Model Package - Fulfilled on Amazon SageMaker
H2O’s AutoML can be used for automating the machine learning workflow, which includes automatic training and tuning of many models within a user-specified time-limit. Stacked Ensembles – one based on all previously trained models, another one on the best model of each family – will be automatically...
Algorithm - Fulfilled on Amazon SageMaker
Significant time is spent by auto insurance adjusters to appraise vehicle loss and estimate the final settlement amount. Large volume of minor loss claims consume significant bandwidth of adjusters. A machine learning model can reduce this amount by inspecting and identifying type of damage after...
Model Package - Fulfilled on Amazon SageMaker
This model was created using data using over 785k records from the cryptocurrency marketing dating all the way back to 2013. The set used for the model uses a market data of over 1600 different cryptocurrencies to help make predictions. With only eight easily accessible and attributes making a...
Model Package - Fulfilled on Amazon SageMaker
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Sensifai offers automatic face recognition and identification. For example, our basic software recognizes thousands of celebrities in images. In Sagemaker platform, you can easily fine-tune this software to recognize a new set of people or celebrities and tag them in images by providing the...
Algorithm - Fulfilled on Amazon SageMaker
Given an input image, this model will generate a mask that describes the category for each pixel. For training new models on your own datasets, the algorithm is also available as built-in SageMaker algorithm: https://docs.aws.amazon.com/sagemaker/latest/dg/semantic-segmentation.html
Model Package - Fulfilled on Amazon SageMaker
Given an incomplete sentence, this model predicts sentences that are most likely to occur in the context. For example, given input "I love it", it will generate samples like "I love it and enjoy one of their series, Schafer or Clive ."
Model Package - 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...
Algorithm - Fulfilled on Amazon SageMaker
Given an input image, this model will return object coordinates and category predictions. The format of coordinates is encoded as (left, top, right, bottom) of the absolute pixel locations. This model is trained on COCO dataset with 80 common object categories. It can be used as fast and reliable...
Model Package - Fulfilled on Amazon SageMaker
Given an input image, this model will return object coordinates and category predictions. The format of coordinates is encoded as (left, top, right, bottom) of the absolute pixel locations. This model is trained on COCO dataset with 80 common object categories. It can be used as fast and reliable...
Model Package - Fulfilled on Amazon SageMaker
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