Emanuele FabbianiSimplifying Forecasts with Teamwork: The Power of Ensemble ModelsJust like in investing, where spreading your bets can lead to rewards without much risk, in the world of machine learning, mixing different…Feb 291Feb 291
Emanuele FabbianiZillow: A Machine Learning Failure?An unbiased analysis of the craziest business downturn driven by machine learning.Jan 22, 2022Jan 22, 2022
Emanuele FabbianiinTowards Data Sciencepytsviz: interactive time series charts with Plotly and PythonIntroducing a new library to speed up time series analysisDec 28, 20211Dec 28, 20211
Emanuele FabbianiinTowards Data ScienceMethod is all you need: 7 mistakes to avoid in Data ScienceA curated collection from our experienceDec 6, 2021Dec 6, 2021
Emanuele FabbianiinTowards Data ScienceStop copy-pasting notebooks, embrace Jupyter templates!Introducing jupytemplate: configurable templates for JupyterFeb 5, 20205Feb 5, 20205
Emanuele FabbianiinTowards Data ScienceIntroducing tsviz, interactive time series visualization in R StudioWhy and how we developed an R Studio add-inJul 27, 20192Jul 27, 20192
Emanuele FabbianiinTowards Data ScienceLessons from a real Machine Learning project, part 2: the traps of data explorationHow to fall into the pitfalls of data exploration and get awayJun 4, 20191Jun 4, 20191
Emanuele FabbianiinTowards Data ScienceLessons from a real Machine Learning project, part 1: from Jupyter to LuigiA brief story about how we realized how to use — and how not not use — Jupyter notebooks in Machine Learning projectsMay 6, 2019May 6, 2019
