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In software engineering, CI/CD generally refers to the common practices of continuous integration and continuous delivery, so all changes are always reviewed and tested.
In our team, we are thriving to improve HW life cycle management by data sciences and have implemented several machine learning models for different business cases, like hardware troubleshoot automation, production deviation detection, etc.
Current management of machine learning models in production requires significant amount of manual work as data is constantly changing and evaluation of different machine learning models is not done systematically. We would like to bring CI/CD concept to machine learning models management based on AB test/multiarmed bandit as part of the evaluation as it has emerged as the predominant method of online testing in the industry today.
Machine learning models performance is compared fairly and a decision is made about whether the new model performs substantially better than the old model. Different AB tests and multiarmed bandit solutions in statistics will be investigated.
In addition, trouble report system is used today internally to troubleshoot hardware or software issues occurring in a hardware at customer unit. Data from this source will be investigated, and new potential features / data points will be evaluated whether and how it can improve current model by the previous developed methodology. Different machine learning models will be tested and modified to needs if necessary.
Improving current models performance is key and evaluation needs to be done in a fair manner.
We are looking for two driven individuals with background in physics/statistics/computer science or a related numerical field at a master’s level together with strong coding skills and problem solving skills. A strong interest and skillset in the field of machine learning and/or statistical modelling is highly advantageous.
This project is suited for two students amount to 60 ECTS credits. The project is planned to start during the first half of January 2020 and the estimated end date is end of June 2020.
If you feel interested, please send in your application as soon as possible.
While applying please attach your updated CV, current grades and cover letter written in English into one document (under CV field in the application tool) and clearly define your technical knowledge.
If you have any additional questions, please contact our Recruiter Elzbieta Penpeska at email@example.com
Steven L. Scott. 2015. Applied Stochastic Models in Business and Industry, vol. 31 (2015), pp. 37-49
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Primary country and city: Sweden (SE) || || Göteborg || Stud&YP
Req ID: 304363