Thiago Cesar's Projects
š Papers & tech blogs by companies sharing their work on data science & machine learning in production.
A curated list of references for MLOps
Codes from the Coursera ML Andrew Ng course
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.
Module and package for dataprep
Project codes used in "The Docker Handbook"
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Repo about generative AI projects
Fit interpretable models. Explain blackbox machine learning.
Interpretable Machine Learning with Python, published by Packt
kedro tests and repos
List of interesting articles on different topics of machine learning and deep learning
Modin: Speed up your Pandas workflows by changing a single line of code
Version Control with Git: week3
Python Data Science Handbook: full text in Jupyter Notebooks
A unified approach to explain the output of any machine learning model.
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
Python class for multiple statistical tests
Tests and implementations using Singular Value Decomposition (SVD)
Config files for my GitHub profile.
Personal website