Marco CerlianiinTowards Data ScienceProxy SHAP: Speed Up Explainability with Simpler ModelsA Practical Guide to Efficient SHAP ComputationSep 211Sep 211
Marco CerlianiinTowards Data ScienceTime Series Forecasting in the Age of GenAI: Make Gradient Boosting Behaves like LLMsApplying zero-shot forecasting with standard machine learning modelsJul 44Jul 44
Marco CerlianiinTowards Data ScienceHitchhiker’s Guide to MLOps for Time Series Forecasting with SklearnHow to develop a time series forecasting project using Scikit-LearnApr 43Apr 43
Marco CerlianiDeploying Kedro Pipelines on Vertex AI: The MLOps journey of a Life CompanyEasy way to scale Kedro projects in productionNov 8, 20232Nov 8, 20232
Marco CerlianiinTowards Data ScienceHitting Time Forecasting: The Other Way for Time Series Probabilistic ForecastingHow long does it take to reach a specific value?Jun 27, 2023Jun 27, 2023
Marco CerlianiinTowards Data ScienceForecasting with Granger Causality: Checking for Time Series Spurious CorrelationsHacking Granger Causality Test with ML ApproachesApr 6, 2023Apr 6, 2023
Marco CerlianiinTowards Data ScienceHacking Causal Inference: Synthetic Control with ML approachesTest Effectiveness of any Treatment over Time with PCAMar 14, 2023Mar 14, 2023
Marco CerlianiinTowards Data ScienceModel Selection with Imbalance Data: Only AUC may Not Save youAre you Searching Parameters Efficiently?Feb 22, 2023Feb 22, 2023
Marco CerlianiinTowards Data SciencePCA for Multivariate Time Series: Forecasting Dynamic High-Dimensional DataSystem Forecasting in Presence of Noise and Serial CorrelationJan 31, 2023Jan 31, 2023
Marco CerlianiinTowards Data ScienceHacking Statistical Significance: Hypothesis Testing with ML ApproachesTest Statistical Significance in any Context Without AssumptionsJan 10, 2023Jan 10, 2023
