"This solution uses Claude 2.1, a Large Language Model to extract intricate financial data from stock analyst reports. By leveraging the prowess of generative pre-trained transformers, this solution accurately retrieves information from various lengthy and complex stock analyst reports supplied in...
Model Package - Fulfilled on Amazon SageMaker
This post-pandemic Propensity Model determines the probability that a US adult Watches Pro Golf. Lift over Random 2.57. 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 solution solves crew rostering problem due to flight time variability or flight delays. It minimizes the changes in the existing crew schedule to provide the optimum revised schedule for each crew member
Model Package - Fulfilled on Amazon SageMaker
This Pandemic Propensity Model determines the probability that a US adult is Comfortable Going to Beauty Salons & Barber Shops. Lift over Random 1.32 This Pandemic Propensity model is one of a series of consumer classification models based on data from over 31,000 US adults surveyed between April...
Model Package - Fulfilled on Amazon SageMaker
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Singular Value Decomposition based dimensionality reduction on sparse data set like LibSVM 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
Genetic variants found in patient samples contain assertions made regarding their clinical significance, information about the submitter, and other supporting data. These variants are classified by clinical laboratories on a categorical spectrum ranging from benign, likely benign, uncertain...
Model Package - Fulfilled on Amazon SageMaker
This is an object detection model from [TensorFlow Hub](https://tfhub.dev/tensorflow/centernet/hourglass_1024x1024_kpts/1). It takes an image as input and returns bounding boxes for the objects in the image. The model is pre-trained on COCO 2017 which comprises images with multiple objects and the...
Model Package - Fulfilled on Amazon SageMaker
Identify customers most likely to complain after a disruption/service failure and proactively reach out to them to improve customer satisfaction, reducing the number of complaints made to the call center. Identify those customers/agents who take advantage of the flexibility allowed by airlines to...
Model Package - Fulfilled on Amazon SageMaker
Mphasis DeepInsights Named Entity Recognizer is an efficient way of identifying named entities present in the corpus of text. This solution applies NLP techniques to extract the named entities which can be used for further text analytics and for providing useful insights about the text. The model...
Model Package - Fulfilled on Amazon SageMaker
This is an Image Classification model from [TensorFlow Hub](https://tfhub.dev/google/bit/m-r50x3/ilsvrc2012_classification/1). It takes an image as input and classifies the image to one of the multiple classes. The model available for deployment is pre-trained on ImageNet which comprises images of...
Model Package - Fulfilled on Amazon SageMaker
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