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Machine Learning
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for Education
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Electronics & Electrical Engineering
- Analog Electronics Basics Lab
- Digital Electronics Lab
- Digital Logic Lab
- Electronics Engineering Lab
- Electronics Engineering Lab (Components)
- Fault Detection and Correction Lab based on NI ELVIS
- Fault Detection and Correction Lab based on NI VirtualBench
- Industrial Electronics Lab
- Instruments Calibration Lab
- Interface Indication and Control Lab
- Microcontrollers Application Lab
- Operational Amplifiers Applications Lab
- Operational Amplifiers Lab
- Power Electronics Lab
- ADC/DAC Lab
- Three-Phase Circuits Lab
- Arduino Applications Lab
- Mechanical Engineering
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Control & Measurement
- Control System Principles Lab
- Data Analysis Tool for Researchers "DAnS"
- Electrical Measurements Lab based on NI VirtualBench
- Electronic Components Characterization Lab based on NI ELVIS
- Electronic Components Characterization Lab based on NI VirtualBench
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Industrial Application
- “InPEduS” Industrial Protocols Educational Software
- Automated Production System
- Conveyor Stand for Research of Industrial Communications
- Industrial and Avionic Protocols Educational Software
- Industrial Electronics Lab
- Industrial IoT Lab. Basic Version
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Machine Learning Lab based on NI ELVIS
New product
Machine Learning gained more popularity in the industrial applications in the past couple of years. This course helps students and engineers working in the field to learn and try the algorithms that are being used in industry.
Machine Learning gained more popularity in the industrial applications in the past couple of years. This course helps students and engineers working in the field to learn and try the algorithms that are being used in industry.
With the help of vibration simulator, it is possible to simulate different types of faults in the system and collect real data from the accelerometers that are mounted on the motor. Trainees will be able to train the model with various algorithms and deploy it for system health prediction.