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Feature Generation with Gradient Boosted Decision Trees

less than 1 minute read

Published:

In this blog, we implement an idea previously mentioned in a Facebook AI research paper: Practical Lessons from Predicting Clicks on Ads at Facebook The idea is to create non-linear transformations of features using a gradient boosting decision tree that is then used to predict with a final estimator. The implementation is a python pipeline transformer hosted in the sktools package

Questions on Explainable AI

less than 1 minute read

Published:

May Edition: Questions on Explainable AI As machine learning models penetrate almost every area of knowledge, actually understanding what ML systems do starts to seem problematic

Isolation Forest From Scratch

less than 1 minute read

Published:

Implementation of Isolation forest from scratch for further understanding of the algorithm

portfolio

publications

talks

Quantile Encoder: Tackling High Cardinality Categorical Features

Published:

In this paper, we provide an in-depth analysis of how to tackle high cardinality categorical features with the quantile. Our proposal outperforms state-of-the-art encoders, including the traditional statistical mean target encoder, when considering the Mean Absolute Error, especially in the presence of long-tailed or skewed distributions

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.