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The purpose of this project is to engineer a Python pipeline for analyzing stock data. The machine learning team intends to process terabytes of data and integrate it with daily news headlines to assess the reliability of sentiment analysis in predicting stock prices. The team has opted for a Python-based approach, emphasizing the the flexibility and simplicity of implementation. The completion of this project involves refining and expanding existing python classes to handle the analysis task differently. The civic impact lies in the potential enhancement of stock prediction models, contributing to more informed financial decisions for both individual and institutional investors in the Portuguese market.
- Inferential Statistics
- Machine Learning
- Data Visualization
- Predictive Modeling
- etc.
- R
- Python
- D3
- PostGres, MySql
- Pandas, jupyter
- HTML
- JavaScript
- etc.
- Implementation of statistical metrics
- Comprehensive understanding of stock data dynamics
- Debugging