cerlymarco/MEDIUM_NoteBook

Repository containing notebooks of my posts on Medium

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This repository offers a collection of Jupyter notebooks that demonstrate advanced machine learning techniques specifically tailored for time series analysis and forecasting. It provides practical code examples for tackling challenges like predicting future trends, understanding causality, and managing data quality issues. Data scientists, machine learning engineers, and quantitative analysts can use these notebooks to learn and apply sophisticated methods to their time-series-driven projects.

2,138 stars. No commits in the last 6 months.

Use this if you are a data scientist or ML engineer looking for detailed, code-based examples to implement advanced time series forecasting, causality analysis, or model interpretability techniques.

Not ideal if you are looking for a plug-and-play software tool or a general introduction to basic machine learning concepts, as this content is aimed at practitioners with existing technical knowledge.

time-series-forecasting causal-inference machine-learning-operations model-explainability predictive-analytics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Jupyter Notebook

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MIT

Last pushed

Sep 22, 2024

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