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umap-hdbscan

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Implemented machine learning across HR, Sales, Marketing, and PR to improve decision-making. Used models like XGBoost, Prophet, LSTM, clustering, and NLP to enhance retention, forecasting, segmentation, and sentiment analysis for business growth.

  • Updated Jun 13, 2025
  • Jupyter Notebook

Developed an unsupervised pipeline that clusters financial headlines into 100+ meaningful topics using BERTopic and HDBSCAN. Integrated sentiment analysis to track market sentiment volatility and visualize topic trends across stock tickers and time. Combined multiple datasets to create a scalable, finance-ready insight system

  • Updated May 26, 2025
  • Jupyter Notebook

Bachelor thesis is submitted in fulfilment of the requirements for the Bachelor of Science degree in the Department of Business Analytics and Information Technologies at the Faculty of Applied Sciences of Ukrainian Catholic University.

  • Updated Apr 30, 2025
  • Python

This repository explores machine learning applications in HR, Sales, Marketing, and PR to improve decision-making. It features models for predicting employee turnover, forecasting sales trends, and customer segmentation. 🐙📊

  • Updated Jun 21, 2025
  • Jupyter Notebook

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