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Repositório destinado a consolidar parte dos materiais utilizados em disciplinas ministradas no CEUB

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UniCEUB

Repositório destinado a consolidar parte dos materiais utilizados em disciplinas ministradas no UniCEUB. A lista de materiais de apoio (abaixo) está em constante atualização. Sugestões são sempre bem-vindas!

contributions welcome

Materiais externos 📚

Cálculo

  1. Understanding the Gradient Better Explained
  2. Mathematics for Machine Learning Deisenroth et al., 2020

Álgebra Linear

  1. Linear Models in Statistics Rencher & Schallje, 2008

Machine Learning

  1. The Elements of Statistical Learning Trevor et al., 2009
  2. Statistical Learning with Sparsity: the Lasso and Generalizations Trevor et al., 2015
  3. Deep Learning Goodfellow et al., 2016
  4. Aprendizado de Máquina: Uma Abordagem Estatística Izbicki & dos Santos, 2020
  5. An Introduction to Statistical Learning (applications in R) James et al., 2021
  6. An Introduction to Statistical Learning (applications in python) James et al., 2023

Causal Inference

  1. Causal Inference for The Brave and True Matheus Facure, 2022
  2. Causal Inference: What If Hernán & Robins, 2024
  3. Causal ML Book Chernozhukovet al., 2024
  4. Causal Inference: The Mixtape Cunningham, 2021

Programação

  1. Python Data Science Handbook Jake VanderPlas, 2016
  2. R for Data Science Wickham & Grolemund, 2017
  3. Hands-on Machine Learning with R Boehmke & Greenwell, 2019
  4. Python para Estatísticos Telmo Menezes, 2021
  5. Python for Data Science Arthur Turrell, 2022

Vídeos 📺

  1. Machine Lerning Full Course, Stanford CS229 Taught by Andrew Ng (Autumn 2018)
  2. StatQuest, breaking down complicated Statistics and Machine Learning into small pieces that are easy to understand StatQuest with Josh Starmer

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