caionobrega's starred repositories
data-scientist-handbook
This is a repo with links to everything you'd ever want to learn about data science
ML-Papers-Explained
Explanation to key concepts in ML
llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
system-design
Learn how to design systems at scale and prepare for system design interviews
system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
guiadevbrasil
Um guia extenso de informações com um vasto conteúdo de várias áreas para ajudar, agregar conhecimento e retirar dúvidas, nesse guia você encontrará tudo que necessário para qualquer carreira relacionada a tecnologia.
trabalhando-remoto
Informações para quem trabalha ou quer trabalhar remoto
AutoML-Tutorial
Tutorials about AutoML
nlp-recipes
Natural Language Processing Best Practices & Examples
ml-engineer-roadmap
WIP: Roadmap to becoming a machine learning engineer in 2020
list_of_recommender_systems
A List of Recommender Systems and Resources
maza-ad-blocking
Simple, native and efficient local ad blocker. Only Bash.
build-your-own-x
Master programming by recreating your favorite technologies from scratch.
machine-learning-systems-design
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"
awesome-data-labeling
A curated list of awesome data labeling tools
Data-Analysis
Data Science Using Python
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
desafio-eng-de-dados
Desafio para Engenheiro(a) de Dados - VAGAS.com
NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.