Mini workshop to provide a peak of what’s happening under the hood of models currently at the frontier of the AI revolution, and about how we can track the emissions of our own code.

A Satellite Semantic Segmentation Project using Unet and Attention Unet with Pytorch,

Make an impact with a single API call — plant trees, clean oceans, capture CO₂, and donate to global causes.

Energy Consumption of various Machine Learning and Deep Learning Models using codecarbon

[EARLY ACCESS] vscode extension for codecarbon

Make an impact with a single API call — plant trees, clean oceans, capture CO₂, and donate to global causes.

This project develops forecasting models for monitoring forest health, focusing on Larch Casebearer damage using Yolov8 models, with a focus on evaluating the environmental impact of the training process

Codebase for the MLCost application developed for my thesis for the Telecommunications Enginnering bachelor, Universidad Rey Juan Carlos

A tool to measure and compare the energy consumption of Python code variants, with a focus on identifying the impact of code smells.

Carbon-aware machine learning benchmarking framework evaluating predictive performance alongside energy consumption and CO₂ emissions.

Diving into the world of Tracking CO2 Emissions from our software or code. Code Carbon is a lightweight open-source Python Library that lets you track the Co2 emissions produced by running code.

End-to-end ML pipeline for predicting house prices using the Ames Housing dataset.

The system tracks the emissions of a given recommendation algorithm on a given dataset.

This study analyzes the energy efficiency (E(n)) of MergeSort and QuickSort on Apple M2 architecture. While QuickSort is faster for large datasets (N=50,000), it consumes significantly more energy (3.75 J) than MergeSort (2.50 J) due to higher instantaneous power draw. It highlights the need for energy-aware algorithm selection.

MakeImpact is a Python SDK that helps you integrate environmental actions into your applications. 🌱 With simple commands, you can easily contribute to sustainability efforts, like planting trees and cleaning oceans. 🐙

Example project built as a tutorial on how to monitor the emissions and energy consumption of a Python application, using AWS CloudWatch to increase the visibility of these statistics using Custom Metrics and Dashboards.

Pytest plugin for tracking carbon emissions

Experiments to measure the energy consumption of various privacy-enhancing technologies

Terraform module to deploy CodeCarbon as a DaemonSet on Kubernetes to monitor carbon emissions across all nodes.