Open in app

Sign In

Write

Sign In

Adrien Biarnes
Adrien Biarnes

638 Followers

Home

About

Published in MLearning.ai

·Pinned

Building a Multi-Stage Recommendation System (Part 1.1)

Understanding candidate generation and the two-tower model — Introduction In this blog post, we will first discover why multi-step recommendation should be the go-to strategy for companies with large item catalogs. Then we will move on to describe one of the famous latest architecture for candidate generation, namely the two tower architecture. …

Machine Learning

15 min read

Building a Multi-Stage Recommendation System (Part 1.1)
Building a Multi-Stage Recommendation System (Part 1.1)
Machine Learning

15 min read


Published in Towards Data Science

·Mar 11

A Complete Tutorial on Off-Policy Evaluation for Recommender Systems

How to reduce the offline-online evaluation gap — Introduction In this tutorial, I will give some rationales about why one should care about off-policy evaluation. Then I’ll introduce the right amount of theory on the matter. I will not dive too deep into the latest methods and stop on what works well empirically. …

Machine Learning

18 min read

A Complete Tutorial on Off-Policy Evaluation for Recommender Systems
A Complete Tutorial on Off-Policy Evaluation for Recommender Systems
Machine Learning

18 min read


Published in MLearning.ai

·Sep 27, 2022

Building a multi-stage recommendation system (part 2.1)

Heavy ranking model strategy and design — Multi-gate Mixture-of-Experts In the first post of this series, we learned about the importance of adopting a multi-stage recommendation strategy, especially for companies with large item catalogs. We learned what candidate generation was and implemented one of its famous representatives: the two-tower model…

Machine Learning

11 min read

Building a multi-stage recommendation system (part 2.1)
Building a multi-stage recommendation system (part 2.1)
Machine Learning

11 min read


Published in MLearning.ai

·Aug 25, 2022

Building a multi-stage recommendation system (part 1.2)

Implementation of the two-tower model and its application to H&M data — This blog post is the follow-up on part 1.1 where we explained the two-stage recommendation process with a special emphasis on the candidate generation step. I encourage you to read this article first if you didn’t already. We described the two-tower model in depth and we are now going to…

Machine Learning

14 min read

Building a multi-stage recommendation system (part 1.2)
Building a multi-stage recommendation system (part 1.2)
Machine Learning

14 min read


Published in Towards Data Science

·Feb 10, 2021

How CatBoost encodes categorical variables?

One of the key ingredients of CatBoost explained from the ground up — CatBoost is a “relatively” new package developed by Yandex researchers. It is pretty popular right now, especially in Kaggle competitions where it generally outperforms other gradient tree boosting libraries. Among other ingredients, one of the very cool feature of CatBoost is that it handles categorical variables out of the box…

Statistics

17 min read

How CatBoost encodes categorical variables?
How CatBoost encodes categorical variables?
Statistics

17 min read


Published in Towards Data Science

·Jan 26, 2021

From Boosting to GradientBoosting

A friendly but rigorous explanation — This article is intended for either students trying to break into data science or professionals in need of a refresher on boosting and gradient boosting. There are already quite a lot of materials regarding this topic on the web but not many include graphical visualization of the learning process. So…

Machine Learning

11 min read

From Boosting to GradientBoost
From Boosting to GradientBoost
Machine Learning

11 min read


Published in Towards Data Science

·Oct 14, 2020

Multinomial Mixture Model for Supermarket Shoppers Segmentation

A complete tutorial — In my last article, I wrote a detailed explanation of the Gaussian Mixture Model (GMM) and the way it is trained using the Expectation-Maximization (EM) algorithm. This time, I wanted to show that a mixture model is not necessarily a mixture of Gaussian densities. It can be a mixture of…

Bayesian Statistics

31 min read

Multinomial Mixture Model for Supermarket Shoppers Segmentation (A complete tutorial)
Multinomial Mixture Model for Supermarket Shoppers Segmentation (A complete tutorial)
Bayesian Statistics

31 min read


Sep 21, 2020

EM 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 article might not be very useful. The goal here is to derive the closed-form expressions necessary for the update of the parameters during the Maximization step of the EM algorithm…

Statistics

5 min read

EM of GMM appendix (M-Step full derivations)
EM of GMM appendix (M-Step full derivations)
Statistics

5 min read


Published in Towards Data Science

·Sep 11, 2020

Gaussian Mixture Models and Expectation-Maximization (A full explanation)

In the previous article, we described the Bayesian framework for linear regression and how we can use latent variables to reduce model complexity. In this post, we will explain how latent variables can also be used to frame a classification problem, namely the Gaussian Mixture model (or GMM in short)…

Statistics

16 min read

Gaussian Mixture Models and Expectation-Maximization (A full explanation)
Gaussian Mixture Models and Expectation-Maximization (A full explanation)
Statistics

16 min read


Published in Analytics Vidhya

·Aug 7, 2020

Latent Variables Probabilistic Modeling

Over the past year, I have taken more and more interest in Bayesian statistics and probabilistic modeling. Along this journey, I have encountered the latent probabilistic models. We will start by explaining the concept of a latent variable. And to properly understand its benefits we need to make sure that…

Bayesian Statistics

10 min read

Latent probabilistic modeling (Part 1)
Latent probabilistic modeling (Part 1)
Bayesian Statistics

10 min read

Adrien Biarnes

Adrien Biarnes

638 Followers

I am a machine learning engineer at Dailymotion working on large scale deep recommender systems — https://www.linkedin.com/in/adrien-biarnes-81975717

Following
  • Cassie Kozyrkov

    Cassie Kozyrkov

  • Sergi Castella i Sapé

    Sergi Castella i Sapé

  • Luís Roque

    Luís Roque

  • Marco Cerliani

    Marco Cerliani

  • Pinterest Engineering

    Pinterest Engineering

Help

Status

Writers

Blog

Careers

Privacy

Terms

About

Text to speech