farmvibes-ai
Geo ML Framework
A framework for building geospatial machine learning models that fuse multiple datasets to gain insights into agriculture and sustainability
FarmVibes.AI: Multi-Modal GeoSpatial ML Models for Agriculture and Sustainability
694 stars
37 watching
123 forks
Language: Jupyter Notebook
last commit: 3 months ago
Linked from 2 awesome lists
agricultureaigeospatialgeospatial-analyticsmulti-modalremote-sensingstacsustainabilityweather
Related projects:
Repository | Description | Stars |
---|---|---|
| Curated resources and code projects for machine learning in geospatial data science | 564 |
| A Python framework providing access to public agricultural datasets and pre-trained models for deep learning tasks. | 189 |
| A framework for building and evaluating machine learning systems with high accuracy and interpretability, particularly in human-centered applications. | 13 |
| A collection of geospatial data and supporting documentation for environmental sustainability and Earth science applications | 287 |
| Tools for building machine learning solutions on satellite imagery | 81 |
| A framework for analyzing land eligibility in the context of renewable energy systems using geospatial data | 51 |
| A specification and implementation framework for streaming massive heterogeneous 3D geospatial datasets | 2,164 |
| An advanced agricultural modeling framework built in C# | 140 |
| A framework and benchmark for training and evaluating multi-modal large language models, enabling the development of AI agents capable of seamless interaction between humans and machines. | 305 |
| A machine learning framework for native code on Macs with support for neural networks and natural language processing. | 37 |
| A modular framework for modeling global land systems and agricultural production's impact on the environment | 101 |
| Automates the setup and training of machine learning algorithms on remote servers | 316 |
| A framework for simplifying machine learning development and deployment | 207 |
| A framework for hosting and training machine learning models on a blockchain, enabling secure sharing and prediction without requiring users to pay for data or model updates. | 559 |
| A curated collection of research papers, articles, and resources on machine learning systems, including design principles, infrastructure, and best practices. | 2,710 |