RecommendationEngine | Recommendation Engine using Azure ML Studio | Recommender System library

 by   dotnet-architecture C# Version: Current License: No License

kandi X-RAY | RecommendationEngine Summary

kandi X-RAY | RecommendationEngine Summary

RecommendationEngine is a C# library typically used in Artificial Intelligence, Recommender System applications. RecommendationEngine has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Recommendation Engine using Azure ML Studio to recommend related movies. The app relies on using the popular MovieLens 20M dataset. The Azure Machine Learning model was built using the TrainBox Match Recommender which is a hybrid recommender. It uses both user-content and colloborative filtering to provide recommendations out-of-the-box. You can find more details about the app and how the Azure Machine Learning recommendation model is built through this blog.
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              RecommendationEngine has a low active ecosystem.
              It has 76 star(s) with 40 fork(s). There are 17 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              RecommendationEngine has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of RecommendationEngine is current.

            kandi-Quality Quality

              RecommendationEngine has 0 bugs and 0 code smells.

            kandi-Security Security

              RecommendationEngine has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              RecommendationEngine code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              RecommendationEngine does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              RecommendationEngine releases are not available. You will need to build from source code and install.

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            RecommendationEngine Key Features

            No Key Features are available at this moment for RecommendationEngine.

            RecommendationEngine Examples and Code Snippets

            No Code Snippets are available at this moment for RecommendationEngine.

            Community Discussions

            QUESTION

            deploy predictionio with spark standalone cluster
            Asked 2018-May-22 at 10:13

            I use the official Recommendation as a test. I did these steps successfully:

            1. event server installed in a docker container.(successfully)
            2. config eventdata, metadata and all things are stored in mysql.(successfully)
            3. train & deploy server in another docker container.(successfully)
            4. spark standalone cluster installed in another container.(successfully)
            5. create new app.(successfully)
            6. import enough eventdata.(successfully)

            When I train and deploy as follows, it's ok as the docs described :

            ...

            ANSWER

            Answered 2018-May-22 at 10:13

            step-deploy depends on step-train's datas written at file://tmp or hdfs://tmp.

            Source https://stackoverflow.com/questions/50256449

            QUESTION

            PredictionIO Training Error: ArrayIndexOutOfBoundsException
            Asked 2017-Jul-15 at 11:37

            We have a PIO 0.11.0 instance running, and we are attempting to use the UR engine, version 0.6.0 (https://github.com/actionml/universal-recommender). We have loaded the eventserver up with our training data, and when we run pio train the following error is produced:

            ...

            ANSWER

            Answered 2017-Jul-15 at 11:37

            PIO can not find any purchase events in your data (may be they have wrong format). As result it can't build correlation between users & items.

            Can you show sample events?

            Source https://stackoverflow.com/questions/45016344

            QUESTION

            Second Autowired REST Repository not working
            Asked 2017-May-15 at 15:29

            I am using inside of my application's controller autowired repository that works fine. But I also want to use my repo inside of another class. But when I invoke any method from the second class I get null pointer exception, looks like Autowiring is not working inside of this class. What am I doing wrong? Is it impossible to Autowire the same repo more than once? Or maybe I should implement Service and call my repo via Service?

            Error:

            ...

            ANSWER

            Answered 2017-May-15 at 15:14

            Q : But when I invoke any method from the second class I get null pointer exception, looks like Autowiring is not working inside of this class. What am I doing wrong?

            A : It's normal, as your RecommendationEngine class is not a spring bean ==> not handled by the spring context. So to make it works you should configure it as a bean ( using annotation or xml config ).

            Q : Is it impossible to Autowire the same repo more than once?

            A : You can call your spring beans as many as you want.

            Source https://stackoverflow.com/questions/43982843

            QUESTION

            How to get string values in RDD while implementing spark fp growth?
            Asked 2017-Mar-28 at 20:20

            I have successfully joined userID with match in the query below.

            ...

            ANSWER

            Answered 2017-Mar-28 at 20:20

            You have a row with 2 fields, and row.get(2) gets the value of its third field (fields in row are 0-based, as usually); of course it's an error. To get matchesPlayedOn, use row.get(1) or just row(1).

            Source https://stackoverflow.com/questions/43058171

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install RecommendationEngine

            You can download it from GitHub.

            Support

            As mentioned, we'd appreciate to your feedback, improvements and ideas. You can create new issues at the issues section, do pull requests and/or send emails to aasthan@microsoft.com.
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            gh repo clone dotnet-architecture/RecommendationEngine

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            git@github.com:dotnet-architecture/RecommendationEngine.git

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