The MLHub repository hosts the following currated pre-built machine learning models. Try them out and let us know if you have any issues. They are easily and quickly installed and demonstrated. Feedback is welcome through github. Visit MLHub.ai for details.
Anyone can create a MLHub package simply by including a MLHUB.yaml file in their github repository. The models listed here are currated in by MLHub administrators. If you find any issues do be sure to report them.
Name | Version | Description |
---|---|---|
animate | 2.1.5 | Tell a data narative through animations |
audit | 4.1.0 | Classic financial audit predictive classification model. |
azanomaly | 3.1.4 | Azure Anomaly Detection. |
azcv | 2.7.2 | Azure Computer Vision. |
azface | 2.2.1 | Azure Face API demo. |
azlang | 0.0.4 | Azure language cognitive service on the cloud. |
azspeech | 4.4.1 | Azure Speech cognitive services on the cloud. |
aztext | 2.5.2 | Azure Text Analytics cognitive services on the cloud. |
aztranslate | 2.5.3 | Azure Text Translation cognitive services on the cloud. |
barchart | 2.0.2 | Demonstrate the concept of barcharts. |
beeswarm | 2.0.1 | Demonstrate the concept of bee swarm charts. |
bing | 0.1.5 | Bing Maps |
cars | 1.0.0 | Identify car make and model from a photo. |
colorize | 1.5.9 | Demonstrate the concept of photo colorization. |
cvbp | 2.2.0 | Computer vision best practices. |
deepspeech | 0.0.3 | Deepspeech |
easyocr | 0.0.8 | Extract text from images. |
facedetect | 0.2.5 | Simple face detection. |
facematch | 0.4.2 | Simple face recognition. |
0.0.1 | Google Maps | |
iris | 2.1.3 | Classic iris plant species classifier. |
kmeans | 0.3.0 | An animation demonstration for the kmeans clustering |
movies | 2.0.4 | Movie recommendation using the SAR algorthm. |
objects | 1.6.27 | Recognise objects in an image using resnet152. |
ocsvm | 0.0.5 | Introducing one-class support vector machine. |
opencv | 1.0.3 | OpenCV Computer Vision. |
patientpaths | 0.0.8 | Report patient paths for specific scenarios. |
ports | 2.0.2 | Demostrate the concept of visualising data. |
pyiris | 0.0.8 | Classification models in Python using the iris dataset. |
pyspeech | 0.1.3 | Convert audio speech to text across multiple services. |
rain | 5.1.4 | Predict if it will rain tomorrow (decision tree and rand... |
rbm | 1.0.6 | Recommendations using restricted Boltzmann machine. |
sar | 1.1.6 | Smart adaptive recommendations. |
scatter | 2.0.1 | Demonstrate the concept of scatter plots. |
sgnc | 0.1.1 | Node classification for graphs using StellarGraph. |
tapwater | 0.0.3 | Factor analysis for understanding customers |
webcam | 1.1.0 | Capture video, process, feed dummy device for Zoom. |
zynlp | 0.0.11 | Tweets sentiment analysis. |