AllAccepted answers
Eduard Lebedyuk · Jun 22, 2020

Add a new Business Host. If you want to add several, call CallProductionUpdateAndSaveToClass method once at the end.

Include Ensemble

Class test.prod
{

Parameter DOMAIN = "Ensemble";

/// Add new Business Host.
/// productionName - name of production class
/// name - name of item you want to add
/// class - class name of the item you want to add
/// w $System.Status.GetErrorText(##class(test.prod).add())
ClassMethod add(productionName As %Dictionary.CacheClassname = "isc.py.test.Production", name As %String = "MyOperation", class As %Dictionary.CacheClassname = "isc.py.ens.Operation")
{
    Set production = ##class(Ens.Config.Production).%OpenId(productionName)
    
    Set item = ##class(Ens.Config.Item).%New()
    Set item.PoolSize = 1
    Set item.Name = name
    Set item.ClassName = class
    Set:item.Name="" item.Name = item.ClassName
    Set item.Enabled = $$$YES
    Set sc = production.Items.Insert(item)
    Quit:$$$ISERR(sc) sc
    Set sc = $$$AuditModifyProductionConfig(production.Name,item.Name,$$$Text("Item added to production using generator in " _ $classname()))
    Quit:$$$ISERR(sc) sc   
    Set sc = ##class(EnsPortal.Template.prodConfigSCPage).CallProductionUpdateAndSaveToClass(production,"","SaveProduction")
    Quit sc
}

}
Eduard Lebedyuk · Jun 20, 2020

Here are some ideas for contestants:

  1. MLOperation. Currently, PythonGateway provides low-level PythonOperation aimed at expert users who write Python code themselves. The idea of MLOperation is to build a high-level Interoperability adapter targeted at a broader userbase. Essentially your adapter provides generalized Fit/Predict/Optimize methods and users need to provide the data, target model type, and hyper parameter values. This closes the gap between the hands-off approach of the IntegratedML and low-level approach of the PythonGateway. The work is described in this issue.
  2. New ML language. Interoperability with numerical computational languages or even CASes proper are great and offer the freedom of choice. Furthermore, these math-oriented languages allow faster problem search/space traversal than more generalized languages such as Python. Several classes of supporting ML problems can be solved with them. Callout interface makes implementation process easy (reference implementations: PythonGateway, RGateway, JuliaGateway). Suggested languages: Octave, Scilab. 
  3. New showcases in IoT, Real-Time predictions, RPA. Convergent Analytics group provides a lot of starting templates in these fields - as InterSystems IRIS capabilities are an especially good fit for them. I'm always interested in more examples, especially real-life examples of machine learning.
  4. Data Deduplication solutions. Do you have a dataset with a lot of dirty data and know how to clean it? Great. Make a showcase out of it.
  5. Reinforcement learning showcases. Examples of Partially observable Markov decision process or other reinforcement learning technologies.

 

Also, note that PythonGateway-Template is built upon the Advanced Analytics image, so you can use both IntegratedML and PythonGateway from the same docker image.