#The rtemis ecosystem

rtemis makes advanced machine learning accessible to all - scientists, clinicians, statisticians, computer scientists. It provides:

powerful, low-code APIs: high-level functions with complete controls of the entire data pipeline.
no-code web applications: interactive, user-friendly interfaces.

It is actively used for:

Machine learning algorithm development.
Applied data science, with emphasis on biomedical basic research, clinical predictive modeling, and public health.
Health Data Science education.

rtemis consists of 10 interconnected packages that work together to provide a complete ML ecosystem.

#APIs

rtemis: ML & visualization API in R
rtemis-py: ML & visualization API in Python. (currently private)
rtemis.jl: ML & visualization API in Julia. (currently private)
rtemis.bio: Bioinformatics extension in R
kaimana-r: API access to state-of-the-art open source LLMs in R (currently private)
kaimana-py: API access to state-of-the-art open source LLMs in Python (currently private)
Kaimana.jl: API access to state-of-the-art open source LLMs in Julia (currently private)
kaimana-rs: API access to state-of-the-art open source LLMs in Rust (currently private)

rtemislive: Web application for ML & visualization. (internally deployed at UCSF)
rtemislive-draw: Web Assembly application for interactive data visualization using DuckDB query engine
rtemisSeq: Interactive protein sequence visualization
rtemisXt: Interactive time-series data visualization
kaimana: AI Agent Chatbot using state-of-the-art open source LLMs. (currently private)

Programming for Data Science in R: Beginner- to intermediate-level resource for R programming. Used in UCSF Datasci 213 & 214, among others
Programming for Data Science in Python: Python version (work in progress)
Programming for Data Science in Julia: Julia version (work in progress)

GenLib is a project using kaimana to create AI-generated educational material.

Some screenshots from rtemislive, the Web UI for rtemis:

Loading gallery...