PinnedAdrien BiarnesBuilding a Multi-Stage Recommendation System (Part 1.1)Understanding candidate generation and the two-tower modelAug 13, 20229Aug 13, 20229

Adrien BiarnesinTowards Data ScienceMixture-of-Softmaxes for Deep Session-based Recommender SystemsModern session-based deep recommender systems can be somehow limited by the softmax bottleneck like their language model cousinsJul 18, 2023Jul 18, 2023

Adrien BiarnesinTowards Data ScienceA Complete Tutorial on Off-Policy Evaluation for Recommender SystemsHow to reduce the offline-online evaluation gapMar 11, 2023Mar 11, 2023

Adrien BiarnesBuilding a multi-stage recommendation system (part 2.1)Heavy ranking model strategy and design — Multi-gate Mixture-of-ExpertsSep 27, 2022Sep 27, 2022

Adrien BiarnesBuilding a multi-stage recommendation system (part 1.2)Implementation of the two-tower model and its application to H&M dataAug 25, 20224Aug 25, 20224

Adrien BiarnesinTowards Data ScienceHow CatBoost encodes categorical variables?One of the key ingredients of CatBoost explained from the ground upFeb 10, 20213Feb 10, 20213

Adrien BiarnesinTowards Data ScienceFrom Boosting to GradientBoostA friendly but rigorous explanationJan 26, 2021Jan 26, 2021

Adrien BiarnesinTowards Data ScienceMultinomial Mixture Model for Supermarket Shoppers Segmentation (A complete tutorial)Complete analysis and implementation of a multinomial mixture model for supermarket shopper segmentation and predictive profiles predictionOct 14, 2020Oct 14, 2020

Adrien BiarnesEM of GMM appendix (M-Step full derivations)This article is an extension of “Gaussian Mixture Models and Expectation-Maximization (A full explanation)”. If you didn’t read it, this…Sep 21, 20202Sep 21, 20202

Adrien BiarnesinTowards Data ScienceGaussian Mixture Models and Expectation-Maximization (A full explanation)The full explanation of the Gaussian Mixture Model (a latent variable model) and the way we train them using Expectation-MaximizationSep 11, 20202Sep 11, 20202