BigML vs Slai
Overview
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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 development environment and hosting solution for machine learning models. No servers to manage, no configuration, no headaches. It just works. It is the fastest way to add production-ready ML into an app. |
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) | Production-ready code sandboxes for ML;
One environment for data, dependencies, and code;
Provides source control, giving you a single source of truth for your code and data |
Statistics | |
Stacks 14 | Stacks 2 |
Followers 29 | Followers 6 |
Votes 1 | Votes 0 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
| No integrations available | |
What are some alternatives to BigML, Slai?
NanoNets
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Inferrd
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GraphLab Create
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SAM 3D
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Tinker
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AI Video Generator
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Sportlingo
AI-powered sports analytics and skill assessment API that enables apps and platforms to deliver personalized training, drills, and performance insights.
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.
