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Bitcoin predictor model can help to predict the bitcoin prices based on the time series data. The model is trained with 4 years of data to identify patterns and trends. Tensorflow’s LSTM deep learning model has been used to create the model.

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Go beyond traditional vehicle recognition systems with Deep Vision APIs. We detect cars and recognize the year, make, model, and the angle of vehicles. Leading e-commerce and media brands utilize Deep Vision APIs to enhance product search and organize large collections of data. Advertisers and...

Model Package - Fulfilled on Amazon SageMaker


This model blurs the faces of people in an image to preserve privacy. It was trained on the “Labeled Faces in the Wild” dataset and tested on small and medium sized images. This is a great tool to mitigate privacy concerns when showing images which contain people in a public setting. Please note:...

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7Park Data transaction data parsing allows you to wrangle more value out of your credit card, POS, and receipt data by identifying and extracting key entities. Our transaction data classifier (NER) has been trained and optimized on millions of credit card transactions over the last 5 years....

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Prosper Insights & Analytics' Fashion Conscious propensity model predicts the probability that a U.S. adult consumer is fashion conscious. Based on a set of basic demographics, the model identifies individuals for whom the newest fashion trends and styles are important. The model was trained with...

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This model is designed for automation of business communication. Technical walk-through video describing how to use the model: https://youtu.be/rDdC0ekIBd4 It can serve as basis for classification, automatic responses and other uses. For example see the demo implementation for CRM in Customer...

Model Package - Fulfilled on Amazon SageMaker


This model identifies if a given parking slot is occupied or not. It is trained using convolutional neural network (CNN) on parking lot images to identify occupancy. This model can be extended as edge ML model with a parking monitoring drone that continuously monitors available and occupied parking...

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This algorithm uses the scikit learn framework to predict hospital readmissions from EMR data, DRGs and billing data. The model predicts the probability that a patient will return to the hospital within a certain time period(30 days) or not. The predicted output is the % chance that the patient...

Algorithm - Fulfilled on Amazon SageMaker


Emotion Analysis algorithm uses Natural Language Processing (NLP) to predict the emotion classes from a corpus of text. The algorithm analyses individual text expressions in tweets, comments, etc. made on social media platforms or captured in any other text format to classify across four emotion...

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