Artificial Intelligence (AI) techniques can be used to automate the testing process and achieve smart and intelligent testing system which can test the working of software systems without human intervention.
The applications of AI in analysis of test results have brought tremendous improvements in performance analysis and predicting the behavior of network infrastructure in recent years. Machine learning and deep learning techniques accelerate the process of developing AI applications.
This internship will need the intern to develop the AI applications for the OPNFV testing projects test results. The data for the experiments can be collected from the OPNFV test database. Analytical frameworks like TensorFlow, Keras and Scikit provide library functions for AI application development.
The developed AI applications can be packaged and export as docker files.
For more information about OPNFV Testing projects and Analytical Frameworks please refer:
- Artificial Intelligence
- Data Science
- Deep Learning based AI applications for smart evaluation of OPNFV test results.
- Application for Failure Detection
- Application for Event Correlation
- Application for Root Cause Analysis
- Application for Failure Prediction
- Provides platform for network data analytics.
- Applications Demo and detailed report on AI for OPNFV testing.
Desired project timeline/completion date:
M1 2w : Data Collection and Feature Engineering.
M2 2w: Model Learning, Performance Metrics & Model Validation.
M3 2w: Evaluation of AI Techniques.
M4 1m: Develop application of AI for event correlation and root cause analysis.
M5 1m: Development of Failure Detection and Prediction Applications.
Mentor(s) & contact info: