- Version 1.2
- Sold by Mphasis
This solution is a deep learning-based trainable algorithm which can classify data from multiple sensors and impute missing values.
Mphasis applies next generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis FrontBack™ Transformation approach. 'Front2Back' uses the exponential power of cloud and cognitive to provide hyper-personalized digital experience to clients and their customers. Mphasis Service Transformation approach helps 'shrink the core' through application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world.
This solution is a deep learning-based trainable algorithm which can classify data from multiple sensors and impute missing values.
The solution identify the robustness of ML model towards Membership inference attack which target to extract information about training data
A hybrid quantum computing-based approach for optimal feature selection in machine learning.
This is a Natural Language Processing based solution which can detect up to 10 aspects from online product reviews for cameras.
ML based infrastructure ticket triaging model to improve accuracy of ticket assignments and thereby improve FCR and MTTR.
The solution provides 30 days forecast of server utilization using historical usage data.
This is a Natural Language Processing based solution which can detect up to 12 aspects from online product reviews for dishwashers.
This solution provides 24 hours of forecast of cloud database using historical hourly database resource usage data.
This solution analyzes credit reporting complaints narratives to identify the ones which may require a monetary compensation.
Machine learning based ticket triaging model to improve accuracy of ticket assignments and thereby improve FCR and MTTR.
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