Hello! I'm Christopher L. Luebbers, a researcher specializing in deep learning, natural language processing (NLP), and artificial intelligence. I have a Master's degree in Applied Data Science from Georg-August-Universität Göttingen.

• Deep Learning
• Natural Language Processing
• High-Performance Computing
• Machine Learning

A comprehensive exploration of using R for high-performance data analytics, covering memory management, GPU computing, parallel processing, and comparative analysis with Python. Includes benchmarks, case studies, and code examples.

Investigates the reproducibility of METEOR, BLEU, and ROUGE scores in NLP research. Includes a systematic literature review, software validation testing, and code for analyzing evaluation protocols and packages.

Project for the module "Deep Learning for Natural Language Processing" at Georg-August-Universität Göttingen. Implementations of BERT and sBERT for various NLP tasks, including sentiment analysis, paraphrase detection, and semantic textual similarity.

• Programming Languages: Python, R
• Frameworks: TensorFlow, PyTorch
• Tools: Jupyter Notebooks, Docker, Git, GitHub
• Data Analysis: Pandas, NumPy

• Using R for High-Performance Data Analytics - A seminar report exploring the use of R for high-performance data analytics.
• Meh-Tricks: Towards Reproducible Results in NLP - A research project investigating the reproducibility of evaluation scores in NLP.

Feel free to reach out to me for collaboration, questions, or any interesting discussions!

• Email: [email protected]
• LinkedIn: Christopher L. Luebbers
• Datacamp: christopherluebbers

If you find my projects interesting and want to contribute, feel free to fork the repositories and submit pull requests. Let's collaborate and push the boundaries of AI and NLP research together!

Thank you for visiting my profile. Happy coding!