BigMLWhat is BigML?
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.
BigML is a tool in the Text & Language Models category of a tech stack.
Key Features
REST APIbindings in Pyton, Java, Ruby, node.js, C#, Clojure, PHP, and moreseveral algorithms, including categorical & regression decision trees, ensembles of trees (random decision forest), cluster analysis and moremodels are fully actionable -- translated into code that can be cut/paste for local utilizationPredictServer (and Amazon AMI) can be used for real-time or large batch predictionsmodels can be shared privately or publicly (for free or for a fee set by the developer)
BigML Pros & Cons
Pros of BigML
- ✓Ease of use, great REST API and ML workflow automation
Cons of BigML
No cons listed yet.
BigML Alternatives & Comparisons
What are some alternatives to BigML?
Amazon SageMaker
A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.
Azure Machine Learning
Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.
Amazon Machine Learning
This new AWS service helps you to use all of that data you’ve been collecting to improve the quality of your decisions. You can build and fine-tune predictive models using large amounts of data, and then use Amazon Machine Learning to make predictions (in batch mode or in real-time) at scale. You can benefit from machine learning even if you don’t have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure.
