GNU/Linux Desktop Survival Guide by Graham Williams
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MLHub Available Models

20200220 The available command will list available curated models. These are models that the team behind MLHub review to ensure their integrity and functionality, particularly based on the latest Ubuntu LTS. There is though no limit to what models can be packaged for MLHub. MLHub is able to be pointed to any git repository and install a package based on the MLHUB.yaml file.

$ ml available
The repository 'https://mlhub.ai/' provides the following models:

animate      2.1.4  Tell a data narative through animations                 
audit        4.1.0  Classic financial audit predictive classification model.
azanomaly    3.1.4  Azure Anomaly Detection.                                
azcv         2.3.3  Azure Computer Vision.                                  
azface       2.0.4  Azure Face API demo.                                    
azlang       0.0.3  Azure language cognitive service on the cloud.          
azspeech2txt 2.1.0  Azure Speech to Text cognitive services on the cloud.   
aztext       2.4.1  Azure Text Analytics cognitive services on the cloud.   
aztranslate  2.1.0  Azure Text Translation cognitive services on the cloud. 
barchart     2.0.1  Demonstrate the concept of barcharts.                   
beeswarm     2.0.1  Demonstrate the concept of bee swarm charts.            
colorize     1.5.3  Demonstrate the concept of photo colorization.          
cvbp         1.3.3  Computer vision best practices.                         
facedetect   0.2.5  Simple face detection.                                  
facematch    0.4.2  Simple face recognition.                                
facets       1.0.1  Visualising data using faceted plots.                   
iris         2.1.0  Classic iris plant species classifier.                  
movies       2.0.3  Movie recommendation using the SAR algorthm.            
nlpbp        0.0.2  Natural language processing best practices.             
objects      1.5.6  Recognise objects in an image using resnet152.          
opencv       1.0.2  OpenCV Computer Vision.                                 
ports        2.0.0  Demostrate the concept of visualising data.             
rain_dt      4.0.3  Predict rain tomorrow using a decision tree model.      
rain_rf      2.0.2  Predict rain tomorrow using a random forest model.      
rbm          1.0.6  Recommendations using restricted Boltzmann machine.     
sar          1.1.6  Smart adaptive recommendations.                         
scatter      2.0.0  Demonstrate the concept of scatter plots.               
tapwater     0.0.3  Factor analysis for understanding customers             

To install a named model, local model file or URL:

  $ ml install <model>