BigML vs NanoNets
Overview
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CLI (Node.js)
Manual
Detailed Comparison
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. | Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application. |
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; models are fully actionable -- translated into code that can be cut/paste for local utilization; PredictServer (and Amazon AMI) can be used for real-time or large batch predictions; models can be shared privately or publicly (for free or for a fee set by the developer) | Image categorization API with less than 30 images per category;Custom object localization API;Text deduplication API;Text categorization API |
Statistics | |
Stacks 14 | Stacks 17 |
Followers 29 | Followers 47 |
Votes 1 | Votes 19 |
Pros & Cons | |
Pros
| Pros
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Integrations | |
| No integrations available | |
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