Learning archive · 2020
A guided DataCamp project from my early NLP learning. It is retained to show the analytical foundations that predate my current AI-focused work.
This project applies sentiment analysis to financial-news headlines from Finviz. The objective was to explore how natural-language-processing techniques can classify the tone of headlines and surface a directional view of market sentiment around a stock.
- Preparing headline text for analysis
- Applying sentiment-scoring techniques
- Comparing sentiment patterns across stocks and dates
- Translating model output into a concise analytical interpretation
This is part of my 2020 learning archive. It shows an early interest in language data and applied analytics, while remaining explicit that guided coursework is different from production modelling.