Andressa Marçal's starred repositories
data_engineering_project_template
A template repository to create a data project with IAC, CI/CD, Data migrations, & testing
template_python_project
Esse repositório foi criado com o propósito de servir como um template de um projeto Python.
datacontract-specification
The Data Contract Specification Repository
ydata-profiling
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
100-million-rows-with-spark
Is it feasable to train a model on 100 million ratings using nothing more than a common laptop? Let's find out.
template-e2e-batch
A copier template repository for a e2e batch ZenML MLOps pipeline.
cookiecutter-poetry
A modern cookiecutter template for Python projects that use Poetry for dependency management
machine-learning-systems-design
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"
Python-MLOps-Cookbook
This is an example of a Containerized Flask Application that can deploy to many target environments including: AWS, GCP and Azure.
mlops-credit-risk
MLOps for deploying a Credit Risk model
ollama-docker
Welcome to the Ollama Docker Compose Setup! This project simplifies the deployment of Ollama using Docker Compose, making it easy to run Ollama with all its dependencies in a containerized environment
faststream
FastStream is a powerful and easy-to-use Python framework for building asynchronous services interacting with event streams such as Apache Kafka, RabbitMQ, NATS and Redis.
One-Billion-Row-Challenge-Python
The One Billion Row Challenge using Python
datasets-for-good
List of datasets to apply stats/machine learning/technology to the world of social good.
static-analysis
⚙️ A curated list of static analysis (SAST) tools and linters for all programming languages, config files, build tools, and more. The focus is on tools which improve code quality.
python-causality-handbook-ptbr
Inferência Causal para os Corajosos e Verdadeiros. Uma abordagem divertida, mas rigorosa, para aprender sobre estimativa de impacto e causalidade.