Algolia Recommend vs BigML
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. | It is a robust & flexible API to build unique product recommendations into any digital ecommerce experience. Developers can use a simple and flexible API to build machine learning powered recommendations on your company’s digital storefronts using as few as 6 lines of code, driving better conversions and increasing average order value. It comes with advanced flexibility so you can completely customize the recommendations displayed on your online stores. |
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) | Filter, merchandise, rank and contextualize recommendations to fit your brand and unique business goals; Advanced front-end libraries, API clients, and extensive documentation to help developers build, deploy, and maintain with ease;
Using Algolia Search + Recommend, leverage the same product catalog, merchandising logic, and analytics across search, navigation and recommendations;
Full control, insights for everyone on your team |
Statistics | |
Stacks 14 | Stacks 2 |
Followers 29 | Followers 5 |
Votes 1 | Votes 0 |
Pros & Cons | |
Pros
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Integrations | |
| No integrations available | |
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