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Use NeoPulse® to build models for most types of machine learning problems including, but not limited to, sentiment analysis, object detection, object recognition, classification and regression. Novices and experts can easily create AI models, using custom data, with as little as 14 lines of code in...

Algorithm - Fulfilled on Amazon SageMaker


Based on the dataset and research papers created by Rami M. Mohammad of the School of Computing and Engineering, University of Huddersfield this model uses a range of different website attributes and features to accurately predict whether a website may be a potential phishing site.

Model Package - Fulfilled on Amazon SageMaker


Using the dataset compiled by Hadi Fanaee-T from the University of Porto. The model uses the dataset to help predict the number of rentals for the day based on weather and holiday statistics.

Model Package - Fulfilled on Amazon SageMaker


By using over 280 stats for teams from both games and seasons going back to the 1990’s, this model can help predict the winners and losers for any future NFL matchups. Whether you are trying to get the upper hand in one of your pick-em leagues or just want to see if your favorite team is going to...

Model Package - Fulfilled on Amazon SageMaker


Using over 30,000 records, predict whether a customer will default on their payments. This model uses 23 variables that include gender, education. age, and previous history of payments to generate an accurate predictor of the chances a customer will default, and help you make better decisions as a...

Model Package - Fulfilled on Amazon SageMaker

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Sensifai offers automatic music genre recognition and tagging. For example, our basic software recognizes different categories of music pieces. In Sagemaker platform, you can easily fine-tune this software to recognize a new set of music genres by providing the required training dataset.

Algorithm - Fulfilled on Amazon SageMaker

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The flexible, layered implementation facilitates bar code scanning and decoding for any application. It is for for reading bar codes from various sources, such as video streams, image files and raw intensity sensors. It supports many popular symbologies (types of bar codes) including EAN-13/UPC-A,...

Model Package - Fulfilled on Amazon SageMaker


This model will generate lyrics for your next Billboard-topping single. It was trained on a corpus of songs of 139 artists, including those of many of the 100 most popular artists in America. The API takes two inputs: an artist name and seed words that the song could start with and will generate a...

Model Package - Fulfilled on Amazon SageMaker

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A Random Forest regression on dense data set like CSV without translating the data set into other formats like recordIO. The algorithm scales efficiently across multi-cores on a single AWS EC2 Instance out of the box.

Algorithm - 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