Where to go from here¶
The previous chapters introduced the basic philosophy of the BigML C# bindings and provided a few code samples showing how you can use them to create several kinds of predictions. That was already a wealth of information, but there is much more to learn about BigML REST API and the BigML C# bindings. In the following sections, you will find a few pointer to help you learn about all the features that BigML provides to developers, how to contribute to BigML C# bindings, and more.
BigML is keen to provide all of its users as much information as possible to help them make the best out of its functionality. On BigML web site, you can find thorough guides to all of the features its Dashboard Web UI offers, a number of tutorials ranging from general introduction to ML-techniques to how machine learning can be applied to real-life problems such as churn prediction, loan risk prediction, etc.
BigML REST API¶
BigML provides a rich REST API developers can use to bring the power of machine-learning to their apps. As a proof of the flexibility and power of BigML REST API, it may be interesting to know that BigML web site is entirely based upon them! BigML REST API includes support for advanced machine learning algorithms such as decision trees, ensembles, clusters, anomaly detectors, association rules, and more. Additionally, BigML provides a powerful workflow automation platform based on BigML platform-agnostic DSL for machine learning, WhizzML. You can discover all that BigML REST API has to offer on BigML web site.
Contributing to bindings¶
BigML C# bindings are open-source, and pretty much a constant work in progress given the pace with which BigML feature set keeps growing. If you ever happen to find a bug, or would like to provide a fix or an improvement, you are welcome to clone BigML C# bindings repository on GitHub and send us a pull request.
Also, get in touch for general feedback and to tell us what features you consider most important to have implemented in BigML C# bindings.