|Graduation: Automatic text analysis of text files using machine learning
Assignment type: Graduation
Start date: ASAP
Educational level: WO
Desired study: Computer Science, Data Science, Control Engineer
Language: Dutch or English
Automatically analyze log files using machine learning techniques (NLP) to ease seeing and taking actions for failures in the site. Since XXL systems have complicated infrastructure and architecture, the logging system where the system information is combined becomes long and difficult to analyze by humans. This assignment has impact on time consumption to fix and find the causes of alarms and failures.
Below are a number of research questions that you will be working on during this assignment:
- In any log file how do you find and search the failure cause?
- Where you can classify log files?
- How many types of log files do you want to classify?
You will attend whole lean/agile meetings such as daily, planning, retrospective and system demo meetings to see and plan Loopsorter project’s tasks. Your position will be in the R&D department. Loopsorter project is in cooperation with Service Department and Engineering Department. You will work in the R&D team to support their continuous improvements. Also, you support the enabler for team to make deep analysis for future plans.
Tasks / responsibilities
- Clearly seeing log file pattern(s).
- Easily finding of the failures.
- Saving details for defect solving.
- Collecting historical details in XXL system.
- Analysing and prototyping activities must be done to solve or implement something new in Loopsorter project.
- Integration to code into development areas has to be finished.
- TDD and pair programming practices has to be done within every implementation.
- Student has to plan time to catch deadline.
- Student has to make development test either unit test or component test.
- Bachelor science in computer and data science would be a match.
- Testing and Analyzing skills needed.
- Knowledge of machine learning and deep learning techniques applied to NLP (Natural Language Processing).
- Knowledge of Python (C++ not required).
- Be familiar with following python libraries/tools: numpy, pandas, PyTorch, TensorFlow.
- Be familiar with microservices structure and display layer (optional).
- Knowledge of Docker (optional).
Do you recognize yourself in this challenging profile? And are you looking for an internship/graduation assignment in an organization that has been elected as “Best Employer” for years in a row? Please fill out the application form and upload your resume and cover letter. For more information, contact us by e-mail: firstname.lastname@example.org or Jasper Pijnenburg (Campus Recruiter) by phone: +31 413 49 44 08.