- 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.
This solution predicts sentiments for employee reviews on 5 aspects - career opp, comp & ben, work life balance, work culture & leadership.
This solution analyzes complaint narratives of credit card customers to identify those which may require a monetary compensation.
This is a Natural Language Processing based solution which can detect up to 9 aspects from online product reviews for refrigerators.
Deep Learning based solution to impute missing data in numerical attributes of given structured data.
Computer vision based solution to correct contrast/ brightness in scanned documents to improve performance of document processing pipelines.
This is a Natural Language Processing based solution which can detect up to 7 aspects from online product reviews for camera bags.
This solution can estimate the performance of a machine learning model in production without access to class lable and detect data drift.
The solution analyses customer characteristics to predict which customers are more likely to change their mobile operator.
The solution provides 60 minutes forecast of the network traffic using historic data.
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