machine-learning-optimization-portfolio JordiCorbilla · COMPLETED
This project demonstrates how to optimize a portfolio using a combination of **Machine Learning** and **Mean-Variance Optimization**. By leveraging predictive modeling and statistical methods, the project aims to achieve better **risk-adjusted returns** through dynamic portfolio allocation strategies.
github.com/JordiCorbilla/machine-learning-optimization-portfolio · ★ 2 · Forks 0 · Size 6.6 MB
SUMMARY
Technologies 4
Scored 4
Observed 4
Practices 6
Evidence 4
Skips 0
COVERAGE
Analyzed 10 files · 7 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
2 files · PRODUCTION
NumPy LIBRARY Depth 58
2 files · PRODUCTION
pandas LIBRARY Depth 58
2 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2024-12-30
Last commit 2025-02-09
Active months 3
Commits 7