Hosted machine learning platform with a visual, API-first workflow
BigML is a hosted machine learning platform built around a resource model: datasets, models, ensembles, evaluations and predictions are all objects with URLs, reachable from a web interface, a REST API, bindings in several languages or a command line tool. That uniformity makes automation straightforward - a script can create a dataset, train an ensemble, evaluate it and produce predictions with the same pattern throughout. AutoML, anomaly detection, time series forecasting and topic modelling are available without configuration. It suits teams that want predictive capability through an API without running their own training infrastructure.
Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.
api-driven predictions, tabular automl, forecasting and anomaly detection
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Learning the platform, prototyping a model on a modest dataset and running low-volume predictions. Credits are consumed by training and prediction calls, so a large dataset can exhaust the monthly allowance quickly.
Every artefact is a resource with an identifier, so creating a model and scoring new rows is a sequence of standard HTTP calls. That makes it easy to embed predictions in an application without a separate serving layer.
It is not a deep learning platform. Image, audio and large text models sit outside its core, and teams needing those usually pair it with a framework-based pipeline instead.
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