I am a PhD in Computational Fluid Dynamics turned Data Scientist.
Having a background in academia helps me to understand the data and apply both analytical and creative approaches.
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🔭 I’m currently working on internal company projects.
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I attended an intensive course on Data Science at Constructor Learning, where I stayed on as a TA, then Consultant, and now as a Program Manager. I work with the following technologies (which we also pass on to our students):
- Python, Web Scraping, APIs
- Visualization (incl. Interactive) with Python, Plotly, Bokeh, Streamlit
- Machine Learning - scikit-learn, regression, anomaly detection, clustering, ensemble methods
- Deep Learning - Tensorflow, Keras, neural networks, CNNs, transfer learning, image segmentation, object detection
- Natural Language Processing - text classification, summarization, clustering and similarity, machine translation, sentiment analysis, search and information retrieval, parsing and named entity recognition, classical NLP and transformers
- ML Engineering - SQL, Docker, CI/CD, serving models, MLFlow
- Explainable AI - SHAP, GradCam, Lime, etc
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🌱 I’m currently interested in contributing to open source projects.
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👯 I’m looking to collaborate on interesting Data projects.
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💬 Ask me about how to start a career in Data Science.
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📫 You can reach me on LinkedIn.
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⚡ Fun fact: as a student I organized gothic parties and I still like to participate in creative activities together with other people.