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Bachelor Thesis - SS 2022

MLOps in Recommender Systems: Building a Continuous Training Pipeline with Concept Drift Awareness

Tools: Python, TensorFlow Extended (TFX), TensorFlow Recommenders, Apache Airflow, pandas, NumPy, Matplotlib

Development of a music recommendation generator using the Spotify API. Automated training and deployment of ML models based on real-time monitoring data.

Tools: Python, Delta Lake, Spark, TFX, TensorFlow, Apache Airflow, Google Cloud Platform

Exploratory data analysis, data preprocessing and model training on a used cars dataset. Regression, classification and clustering models were employed.

Tools: Python, pandas, scikit-learn, Matplotlib, Plotly

Development of a prototypical software that identifies and tracks retrieved items from a retail store shelf. This prototype employs a 2-layer architecture using image recognition and image matching.

Tools: Python, OpenCV, YOLOv4

Classification of camera angles and object detection of water splashes in Olympia diving.

Tools: TensorFlow, OpenCV, pandas

Exploratory data analysis, data preprocessing and model training to approximate wine ratings based on their chemical composition.

Tools: Python, pandas, scikit-learn, Matplotlib

Development of a three-layer architecture web-application comprised of a JavaScript frontend using React and a Python backend using Flask + MySQL database. The final application was then deployed and hosted on Google Cloud Platform.

Tools: Python, JavaScript, React, Flask, Google Cloud Platform, MySQL

Certificates

Coursera | 2021

edX | MITx 6.86x | 2020

Scrimba | 2020

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