Gradient may suit individual ML/AI engineers, data scientists, researchers, teams, research groups, and startups building or serving machine learning models.
Best Data Science and Machine Learning Platforms 2026
Every product here is ranked by Samsung Mobile US Press's record score: what its maker publishes about it, where it runs (Android first), whether it is free to try, and how recently the facts were read.
Bioconductor
It suits researchers and data scientists analyzing biological or genomic data with R.
WebWindowsMac+2KNIME Analytics Platform
The free desktop platform suits people building data workflows for personal use.
WindowsMacLinuxDeepnote
Deepnote suits data professionals and teams working with analysis, exploration, or machine learning who want collaborative notebooks, dashboards, or data apps.
WebWindowsMac+4Anaconda Notebooks
It suits learners and Python or data science users who want to work in JupyterLab from a browser.
WebColab may suit students, educators, data scientists, AI researchers, and researchers who want to work with Python notebooks in a browser.
Orange may suit beginners, data scientists, and people learning data science in schools, universities, or professional training.
It may suit teams operating GPU infrastructure for inference, training, fine-tuning, or development workspaces.
It suits enterprises developing and governing AI, especially organizations in regulated industries.
H2O.ai suits businesses, government entities, nonprofits, and academic institutions needing AI development and operations tools.
It suits teams running forecasting, time-series, evaluation, or automated machine-learning workflows on the web.