BigML vs Gradient°: What are the differences?
What is BigML? Machine Learning, made simple. Predictive analytics for big data and not-so-big data. BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.
What is Gradient°? Deep learning platform built for developers. Gradient° is a suite of tools for exploring data and training neural networks. Gradient° includes 1-click Jupyter notebooks, a powerful job runner, and a python module to run any code on a fully managed GPU cluster in the cloud. Gradient is also rolling out full support for Google's new TPUv2 accelerator to power even more newer workflows.
BigML and Gradient° belong to "Machine Learning as a Service" category of the tech stack.
Some of the features offered by BigML are:
- REST API
- bindings in Pyton, Java, Ruby, node.js, C#, Clojure, PHP, and more
- several algorithms, including categorical & regression decision trees, ensembles of trees (random decision forest), cluster analysis and more
On the other hand, Gradient° provides the following key features:
- 1-click Jupyter notebooks
- a powerful job runner
- Python module to run any code on a fully managed GPU cluster in the cloud