The resources available in BigML are the building blocks needed to create a complete Machine Learning solution. You can work with BigML in three different ways: through the Dashboard to easily build your models using the UI, through the REST API whose public domain is hosted in https://bigml.io (or https://au.bigml.io for the Australian site), and through WhizzML to automate your Machine Learning workflows. Below there is a list of all available resources. If you are using the API you can also get this list by typing the URLs mentioned above:
- Modeling preparation:
- Sources
- Datasets
- ML Supervised Models:
- Models (decision trees)
- Ensembles (Bagging, Random Decision Forests, Boosted Trees)
- Logistic Regressions
- Deepnets
- Time Series
- Evaluations
- Single and Batch Predictions
- ML Unsupervised Models:
- Clusters
- Anomalies
- Associations
- Topic Models
- Predictions: Centroids, Anomaly Scores, Association Sets, Topic Distributions
- Statistical Analysis:
- Correlations
- Statistical Tests
- WhizzML REST Resources:
- Libraries
- Scripts
- Executions
Please watch these videos for a gentle introduction to the BigML resources, or read this question to learn more about the BigML models. Additionally, in our detailed documentation we explain how to use these resources through the BigML Dashboard, the API, and WhizzML.