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PhD in Machine Learning
- Brazil
- https://smastelini.github.io/
- https://orcid.org/0000-0002-0092-3572
- in/smastelini
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eng-soft-ml-uel Public
Material das Aulas de Data Science aplicada a Engenharia de Software
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river-extra Public
Forked from online-ml/river-extraExtra functionalities for river
Python BSD 3-Clause "New" or "Revised" License UpdatedApr 17, 2024 -
msts_river Public
Forked from online-ml/river🌊 Online machine learning in Python
Python BSD 3-Clause "New" or "Revised" License UpdatedAug 6, 2023 -
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taxi-demo-rp-mz-rv-rd-st Public
Forked from MaxHalford/taxi-demo-rp-mz-rv-rd-st🚕 Self-contained demo using Redpanda, Materialize, River, Redis, and Streamlit to predict taxi trip durations
Python MIT License UpdatedOct 19, 2022 -
online_learning_intro Public
Introdução a Online Learning - Plantão extra oferecido à turma de 2021 do MBA em Ciência de Dados do ICMC - USP
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river-torch Public
Forked from online-ml/deep-riverPython BSD 3-Clause "New" or "Revised" License UpdatedJun 29, 2022 -
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adwin Public
Candidate ADWIN implementation in pure Python
Jupyter Notebook GNU General Public License v3.0 UpdatedJun 16, 2022 -
awesome-online-machine-learning Public
Forked from online-ml/awesome-online-machine-learning📑 Online machine learning resources
Other UpdatedMar 10, 2022 -
icdm2021_multiway_splits Public
Scripts for reproducing the experiments of our paper at the IncrLearn workshop @ ICDM 2021
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6BSGI_John_Deere_ESALQ Public
Repositório com os códigos e dados utilizados para o desafio da John Deere/ESALQ no 6º Workshop de Soluções Matemáticas para Problemas Industriais - CeMEAI - USP
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streaming_gradient_trees Public
Streaming Gradient Trees (SGT) to appear at river
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scikit-multiflow Public
Forked from scikit-multiflow/scikit-multiflowA multi-output/multi-label and stream data framework. Inspired by MOA and MEKA, following scikit-learn's philosophy.
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BDICMC2019 Public
Link para acesso das práticas: https://drive.google.com/open?id=1hVQWfI5stwAAajslaTRXgdpGnyiSvPsY
Jupyter Notebook UpdatedSep 5, 2019 -
pymfe Public
Forked from ealcobaca/pymfePython Meta-Feature Extractor package.
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