- Version 1.0
- Sold by Mphasis
The solution measures ML robustness towards induction of predesigned noises in the dataset while training classifier on tabular data.
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.
The solution measures ML robustness towards induction of predesigned noises in the dataset while training classifier on tabular data.
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This solution analyzes complaint narratives of credit card customers to identify those which may require a monetary compensation.
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Evaluate privacy awareness with RBAC for an LLM based chatbot such that responses to information seeking queries respect access controls.
Lexicon based NLP solution which analyses customer conversations to identify financial difficulty, vulnerability and forgetfulness.
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