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This comprehensive MLOps suite is designed to enhance and streamline the machine learning lifecycle, from data handling to deployment. Our product offers a robust set of features for the development process, ensuring efficiency, scalability, and security.
Linux/Unix, Ubuntu 22.04 - 64-bit Amazon Machine Image (AMI)
Product Demand Forecasting generates 36 months of forward forecast of the demand using historical data. It uses ensemble ML algorithms with automatic model selection algorithms. This solution provides consistent and better results due to its ensemble learning approach. This solution performs...
Model Package - Fulfilled on Amazon SageMaker
1. Cutting Edge Causal AI A suite of Python packages allow you to perform both identification of causal relationships, as well as estimation of causal effects. decisionOS provides state-of-the-art techniques for performing both causal graph discovery and causal model discovery, with a particular...
Which key parameters need to be closely monitored? What ranges should the parameters stay within? How do I adjust my settings if they deviate? Effective process control holds the answers to all of these questions. It is the key to maintaining process health and achieving peak performance. But...
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This algorithm performs time series forecasting with Liquid Neural Networks (LNNs). It implements both training and inference from CSV data and supports both CPU and GPU instances. The training and inference Docker images were built by extending the PyTorch 2.1.0 Python 3.10 SageMaker containers....
Algorithm - Fulfilled on Amazon SageMaker
This solution provides compositional analysis and predicts the number of incidents pertaining to each ticket group. The insights around incident distribution helps in proper capacity planning, resulting in efficient resource utilization.
Model Package - Fulfilled on Amazon SageMaker
Passenger Traffic Forecasting generates 30 weeks of forward forecast of passengers using historical data. This solution will help businesses such as airlines, railways, bus and ferry operators to better assess the number of incoming passengers and provide them a better travel experience. It uses...
Model Package - Fulfilled on Amazon SageMaker
Absenteeism at work forecasting generates 30 days of forward forecast of employee absenteeism using historical data. This solution helps businesses to optimize their workforce and related infrastructure in an efficient manner. It uses ensemble ML algorithms with automatic model selection...
Model Package - Fulfilled on Amazon SageMaker
Operating Expenses Forecasting generates 30 weeks of forward forecast of the operating expenses using historical data. This will help businesses predict and manage their operating expenses more effectively through better working capital management and improved planning for resource allocation. The...
Model Package - Fulfilled on Amazon SageMaker
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