Flavio Clesio fclesio

Hello, world! My name is Flavio Clesio, aka fclesio.

Personal blog about Machine Learning Engineering, Data Engineering, Culture and Academics.

You can find me on github, twitter, linkedin, medium.

Navigation

• About/Sobre
• Conference Talks
• Contents from Other Authors
• Aforismos / Aphorisms
• Livros / Books

Leitura Recomendada / Recommended Reading

• BaseHTTPMiddleware as Anti-Pattern 2026

• Differential Privacy in R using diffpriv 2023

• Brazilian Heavy Metal: An Exploratory Data Analysis using NLP and LDA 2023

• Multi-Container Pod in GKE to connect to CloudSQL 2022

• Logging and Structured Events in Machine Learning APIs 2022

• livenessProbe and Deadlocks in Machine Learning APIs on Kubernetes 2022

• A Brief Reflection on AutoML 2021

• Machine Learning Operations Active Failures, Latent Conditions 2020

• Security in Machine Learning 2020

• Differential Privacy and Machine Learning 2020

• Cosine Similarity Search for new documents using Scikit-Learn 2020

• Machine Learning and the Swiss Cheese Model: Active Failures and Latent Conditions 2020

• Accountability, Core Machine Learning, and Machine Learning Operations 2020

Recent Posts

• Sabedoria / Wisdom 2026 May 01

• Ozempic 2026 May 01

• Thoughts around second order effects on text 2026 Apr 30

• Practical Machine Learning Models to prevent Revenue Loss 2026 Apr 30

• Machine learning in practice with Spark MLlib (2016) 2026 Apr 30

• BaseHTTPMiddleware as Anti-Pattern 2026 Apr 30

• When even the most seniors don’t know where to go in the AI era 2026 Jan 01

• Quando nem os mais seniores sabem para onde ir na era da IA 2026 Jan 01

• Thank you 2025 Oct 03

• Conflict 2024 Oct 25

Archive

2026

• Sabedoria / Wisdom 2026 May 01

• Ozempic 2026 May 01

• Thoughts around second order effects on text 2026 Apr 30

• Practical Machine Learning Models to prevent Revenue Loss 2026 Apr 30

• Machine learning in practice with Spark MLlib (2016) 2026 Apr 30

• … 3 more →

2025

• Thank you 2025 Oct 03

2024

• Conflict 2024 Oct 25

• Math Youtube Channels 2024 Sep 10

• Interesting Links - Week 01/2024 2024 Jan 07

2023

• Job boards for AI and ML jobs 2023 Aug 28

• Regulamentação de Inteligência Artificial no Brasil 2023 Aug 05

• Artificial Intelligence Regulation in Brazil 2023 Aug 05

• Shaping your algorithms with Debate Devil AI 2023 Jul 24

• consensus.app - An AI tool to search for scientific directions and consensus 2023 Jul 24

• … 21 more →

2022

• Multi-Container Pod in GKE to connect to CloudSQL 2022 Nov 01

• Logging and Structured Events in Machine Learning APIs 2022 Sep 21

• Errors in Election Pools 2022 Sep 09

• Notes, Twitter, and Clipping 2022 Aug 01

• Notas, Twitter e Clipping 2022 Aug 01

• … 5 more →

2021

• ProdOps - ML Products in Production 2021 Dec 25

• Uma breve reflexão sobre o AutoML 2021 Dec 16

• A Brief Reflection on AutoML 2021 Dec 16

• Artigos de ML - Hidden Technical Debt in Machine Learning Systems 2021 Dec 15

• Artigos de ML - The ML Test Score 2021 Dec 14

• … 13 more →

2020

• Security in Machine Learning 2020 Dec 15

• Machine Learning Operations Active Failures, Latent Conditions 2020 Dec 15

• AWS Data Wrangler 2020 Oct 29

• AWS Data Wrangler 2020 Oct 29

• Docker Environment for Data Analysis 2020 Oct 27

• … 35 more →

2019

• Instituto Mises Brazil - An Editorial Analysis Using Natural Language Processing 2019 Dec 10

• Instituto Mises Brasil - Uma análise editorial usando Natural Language Processing 2019 Dec 10

• O Campeonato Brasileiro está ficando mais injusto? (UPDATE FINAL) 2019 Dec 09

• Is the Brazilian Championship getting more unfair? (FINAL UPDATE) 2019 Dec 09

• Some useful tips on how to conduct a systematic review 2019 Nov 04

• … 43 more →

2018

• Siamese Survival Analysis with Competing Risks 2018 Sep 02

• ROC x Precision-Recall 2018 Sep 01

• Machine Learning Tetrad = Business Knowledge + Statistical Understanding + ML Algos + Data 2018 Aug 12

• Understandability of ML models and it’s applications 2018 Aug 11

• Practical advice about research modelling with Andrew 2018 Aug 11

• … 60 more →

2017

• How to make some prediction API using Keras + Flask in 50 lines of code 2017 Dec 17

• How to Build a Prediction API with Keras + Flask in Under 50 Lines 2017 Dec 17

• Como fazer uma API de predição com Keras + Flask em menos de 50 linhas 2017 Dec 17

• PlaidML: An open source portable deep learning engine 2017 Nov 17

• Tensorflow sucks (?) 2017 Nov 15

• … 132 more →

2016

• RLScore: Regularized Least-Squares Learners 2016 Dec 26

• Learning Planar Ising Models 2016 Dec 25

• Sim, você deveria entender o backpropagation! 2016 Dec 24

• Automatic time-series phenotyping using massive feature extraction 2016 Dec 23

• Simple Black-Box Adversarial Perturbations for Deep Networks 2016 Dec 22

• … 49 more →

2015

• O que é ideal no modelo: Acurácia ou Explicabilidade? 2015 Dec 31

• NIPS 2015 2015 Dec 31

• Data Science para perdedores 2015 Dec 31

• 58,484 vezes, OBRIGADO!!! 2015 Dec 30

• 50 Machine Learning API’s 2015 Dec 30

• … 63 more →

2014

• Um post demolidor do Stephen Few sobre o Big Data 2014 Dec 13

• Quando o ruído vira sinal? 2014 Dec 13

• Bases de Dados para Deep Learning 2014 Nov 28

• Por que usar logaritmos? 2014 Nov 25

• Pequenas bases de dados para Toy Problems 2014 Nov 23

• … 101 more →

2013

• Implementação de Self-Organizing Maps 2013 Oct 23

• Correlação não significa necessariamente causalidade 2013 Oct 21

• Story-driven Data Analysis 2013 Oct 17

• Porque você não precisa do Hadoop? 2013 Oct 15

• Predição de Movimentações Criminais 2013 Oct 13

• … 158 more →

2012

• Você deveria terceirizar o setor de análises e inteligência? 2012 Dec 30

• Há conexão entre posse de armas e violência armada? 2012 Dec 29

• Modelos de Segmentação e Classificação 2012 Dec 28

• Agências americanas em conflito devido a programas de mineração de dados 2012 Dec 28

• Mais uma investigação da FTC sobre privacidade infantil e Mineração de Dados… 2012 Dec 27

• … 266 more →

Disclaimer

• Disclaimer/Aviso