Overview
A portfolio of open-source data science projects demonstrating various analytical techniques and machine learning implementations.
Project Categories:
- Predictive Analytics: Time series forecasting, demand prediction, customer churn analysis
- Optimization: Resource allocation, scheduling problems, network optimization
- Machine Learning: Classification, clustering, ensemble methods
- Statistical Analysis: Hypothesis testing, A/B testing, experimental design
Methodologies: Projects showcase best practices in data science including proper train/test splits, cross-validation, hyperparameter tuning, and model evaluation.
Learning & Sharing: These projects serve as both personal learning exercises and contributions to the data science community.
Technologies Used
PythonMachine LearningOptimizationStatistical AnalysisJupyter
Key Features
1
Predictive modeling
2
Optimization algorithms
3
Statistical analysis
4
Machine learning pipelines
5
Code documentation
Impact & Results
Open-source contributions to data science community, demonstrating best practices