AI/Machine LearningMachine Learning uses training and validation data to help a model gain insights to enable it to predict outcomes from similar data patterns. The model uses the learning acquired to forecast future behavior, patterns and trends without being explicitly programmed for this task. The model’s learning can be improved through feedback and retraining to improve the accuracy of its predictions.
SolutionAmper provides a user friendly drag and drop environment to build a flow that can make use of the analytical capabilities of ML model and enables users to connect to other Data Science applications like GE Predix, IBM Watson, to leverage the accuracy and predictive intelligence of their ML models.
Amper also facilitates improving the accuracy of the ML models through its continuous learning capability that allows users to give feedback on model predictions, which can be re-introduced as training data to retrain the model and increase model accuracy. The seamless connectivity between Amper’s process models, data models, event models and ML models presents Amper as a powerful platform that allows the user to take advantage of ML Models to build AI enabled complex business applications.
- Amper’s high scalable algorithms ensure that the system is efficient even if the complexity of the input data increases
- The ML model can be integrated with process, event or data models effortlessly
- Machine Learning model can be integrated with data flow model to enhance data preparation capabilities
- The Event Stream model along with ML model can be used for predictive analysis of live streams of data
- Amper’s AI powered platform automatically determines the best algorithm for a model based on the type of input parameter
- Amper’s visual drag-drop development environment enables quick design of ML model to generate predictions
- Visual representation of the machine learning algorithm and its outcomes, facilitate the user to choose the best ML model
- The prediction intelligence of the model is improvised through continuous learning and re-training.
- When a ML model is re-trained, the Confusion Matrix in Amper forecasts the accuracy of the prediction of the trained model
- Third Party integrations can be done with ease in Amper with the help of API’s
Create actionable event flows or high-speed data-in-motion applications with complex events, simplified through drag-and-drop orchestration.
Build applications that analyze your data-at-rest to uncover newer patterns and models and apply it as micro-services.
A comprehensive process automation suite that provides end-to-end coverage for a variety of complex enterprise business processes.
Discover, interpret, transform and present both streaming data and big data in visually stunning reports with data visualization.
Design and build data flow applications that connect to both traditional databases and big data with multiple layers of security.
Connect to more than 200 disparate systems on the cloud and on-premises to deliver complex applications through easy-to-use libraries.
Complexity of decision logic made simple through comprehensive BRMS that can change and work for you even at run-time!
Next-Gen data analysis and learning through model building and pattern recognition using complex algorithms from standard libraries.