MarianeFurtado
Ph.D. in Epidemiology at the São Paulo School of Public Health; M.A. and B.A. in Economics at the Federal University of Pelotas
@labdaps University of Sao PauloBrazil
Pinned Repositories
Amazing-Feature-Engineering
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Awesome-Federated-Machine-Learning
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
awesome-notebooks
+100 awesome Jupyter Notebooks templates, organized by tools, published by the Naas community, to kickstart your data projects in minutes. 😎
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
azure-ml
Training resources around Azure Machine Learning
best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
cinnamon
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
coding-for-economists
This repository hosts the code behind the online book, Coding for Economists.
MarianeFurtado's Repositories
MarianeFurtado/applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
MarianeFurtado/Awesome-Federated-Machine-Learning
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
MarianeFurtado/awesome-notebooks
+100 awesome Jupyter Notebooks templates, organized by tools, published by the Naas community, to kickstart your data projects in minutes. 😎
MarianeFurtado/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
MarianeFurtado/awesome-python-applications
💿 Free software that works great, and also happens to be open-source Python.
MarianeFurtado/best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
MarianeFurtado/cinnamon
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
MarianeFurtado/coding-for-economists
This repository hosts the code behind the online book, Coding for Economists.
MarianeFurtado/data-focused-python
MarianeFurtado/ElementsOfDataScience
An introduction to data science in Python, for people with no programming experience.
MarianeFurtado/explainerdashboard
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
MarianeFurtado/health_ai_online_pipeline
MarianeFurtado/lecture-python-programming.notebooks
Notebooks for https://python-programming.quantecon.org
MarianeFurtado/lectures
Lecture notes for EC 607
MarianeFurtado/Lectures-Ellis
Lecture Notes (Spring 2021)
MarianeFurtado/ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
MarianeFurtado/ml-glossary
Machine learning glossary
MarianeFurtado/ML-YouTube-Courses
A repository to index and organize the latest machine learning courses found on YouTube.
MarianeFurtado/mlcourse.ai
Open Machine Learning Course
MarianeFurtado/msds621
Course notes for MSDS621 at Univ of San Francisco, introduction to machine learning
MarianeFurtado/NationalOralHealthDataPortal
Data, code, and documentation for the ASTDD National Oral Health Data Portal
MarianeFurtado/pandas_exercises
Practice your pandas skills!
MarianeFurtado/practical-statistics-for-data-scientists
Code repository for O'Reilly book
MarianeFurtado/Python
All Algorithms implemented in Python
MarianeFurtado/Python-1
MarianeFurtado/Sample_Size_and_Power
Sample code for conducting power calculations using in-built commands and simulations
MarianeFurtado/scikit-learn
scikit-learn: machine learning in Python
MarianeFurtado/stat451-machine-learning-fs21
MarianeFurtado/tabnet_fork
A fork of TabNet by Google Research
MarianeFurtado/tabular-transfer-learning
A repo for transfer learning with deep tabular models