Sold by: Miri Infotech
Deployed on AWS
Free Trial
AWS Free Tier
This product has charges associated with seller support and pre-configured products. PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery. Building a production-grade engine to predict users preferences and personalize content for them used to be time-consuming.
Overview
This is a repackaged open source product that incurs additional charges for pre-configured options. It offers a highly tailored, customisable, and one click solution for your needs. Apache PredictionIO is an open source machine learning server used to create predictive engines for any machine learning task. It shortens the time of machine learning application from lab to production by using customizable engine templates which can be built and deployed quickly. It provides the data collection and serving components, and abstracts underlying technology to expose an API that allows developers to focus on transformation components. Once the engine server of PredictionIO is deployed as a web service, it can respond to dynamic queries in real-time.
Highlights
- Infrastructure management
- Support machine learning and data processing
- Unify data from multiple platform
Details
Sold by
Categories
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04LTS
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
Dimension | Cost/hour |
|---|---|
t2.medium Recommended | $0.007 |
t2.micro | $0.007 |
t3.micro | $0.007 |
t3a.micro | $0.007 |
t3.small | $0.007 |
t3a.small | $0.007 |
t2.xlarge | $0.007 |
m4.large | $0.007 |
t2.small | $0.007 |
t2.large | $0.007 |
Dimensions summary
You pay by the hour for the EC2 instance size you run this pre-configured machine learning software on. All 18 options bill the same way; only the underlying instance capacity differs. Sizes range from nano through 2xlarge across the t2, t3, and t3a families, so cost scales with the compute and memory you select. Pick a smaller size for light testing or a larger size for heavier prediction workloads. You are charged only while an instance runs, plus standard AWS infrastructure fees. No fixed term or upfront commitment applies.
Top-of-mind questions for buyers
You get a pre-configured machine learning server built on open source components, ready to create predictive engines. It includes the platform, an event server that gathers data, and an engine server that responds to real-time queries. You access it by connecting to the running EC2 instance over SSH.
You pay the hourly software charge only while an instance runs. A fully stopped instance does not accrue hourly software fees. Stopped instances may still incur standard AWS storage charges for attached volumes, which are separate from this listing's per-hour rate.
No. The software is identical across all 18 sizes. Only the compute and memory of the underlying instance differ. A larger size handles heavier prediction workloads and more data; a smaller size suits light testing. You choose the size during launch based on your capacity needs.
miritech.com
Helpful?
Vendor refund policy
No Refund Policy
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Second Release
Additional details
Usage instructions
Resources
Vendor resources
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.