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pm4py tutorials - tutorial #7 process discovery

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Process Mining for Python

Process Mining for Python

Күн бұрын

In tutorial 7 of the pm4py tutorial series, we look at process discovery in pm4py.

Пікірлер: 21
@kirilproykov1579
@kirilproykov1579 3 жыл бұрын
Interesting tutorials! Thank you for promoting open source PM software!
@processminingforpython1934
@processminingforpython1934 3 жыл бұрын
Thanks for the kind words Kiril!
@nulladdin
@nulladdin Жыл бұрын
Great!
@RafaelFarina87
@RafaelFarina87 2 жыл бұрын
I really enjoy the videos, great work! can you make one about cycle and lead times, or indicate where i can learn more about it within pm4py?
@knowledgesharing6609
@knowledgesharing6609 Жыл бұрын
Excellent Explanation ..Thank you very much for sharing ..regarding Activity duration ..is there any other way that can consider this factor and then generate a model ...
@wallflowercloud
@wallflowercloud 7 ай бұрын
Is there a full set of all the codes that are ran in the videos?
@pedja2518
@pedja2518 2 жыл бұрын
Hi, thank you for the great video series. As a beginner in this area, I have one question. Module pm4py working fine in Atom editor, but it is not recognized in Visual studio code. Maybe, you have answer on that? Thank You
@AdandKidda
@AdandKidda Жыл бұрын
hi, how can i get the generated net plots , in serialized json format for customization ?
@johanquintero1573
@johanquintero1573 Жыл бұрын
Hi mister, how can i discover a petri net model with an event log where resources could be places in the model?
@Rzeshaq
@Rzeshaq 2 жыл бұрын
To me BPMNs look the most intuitive by far. Can't really see why one would use any other types 🤔
@processminingforpython1934
@processminingforpython1934 2 жыл бұрын
Hi Rzeshaq, arguably, the process trees and Petri nets have a more clear 'formal semantics'. Hence, when reasoning (e.g., using a computer) these models are less ambiguous and easier to use. From a practical perspective, i.e., to facilitate communication about a process, BPMN is much much more intuitive indeed!
@vinny2688
@vinny2688 2 жыл бұрын
Can you make a video on conformance checking?
@processminingforpython1934
@processminingforpython1934 2 жыл бұрын
Hi Vinny, yes, that is on our TODO list, we may try to release one in Jan 2022!
@philippstiefel6513
@philippstiefel6513 2 жыл бұрын
@@processminingforpython1934 would be great!
@antonfreyr15
@antonfreyr15 2 жыл бұрын
@@processminingforpython1934 Any updates on a release date? I'm excited.
@processminingforpython1934
@processminingforpython1934 2 жыл бұрын
@@antonfreyr15 we are preparing a new pm4py version (2.3) with some fundamental changes. Alongside, we are updating the docs (proper API docs etc.). We will probably add conformance checking tutorial to our new docs (including a video); Hopefully we manage to do this in Q2 of this year.
@bahaulug6570
@bahaulug6570 3 жыл бұрын
Is it possible to integrate "PM4Py" visualisations in Power BI Desktop, if so can you share a resource please?
@processminingforpython1934
@processminingforpython1934 3 жыл бұрын
Hi Baha, we have been working on integration with Power BI; however, we did not effectively port any visualizations, i.e., the integration passes pandas df's back and forth.
@ladesalir
@ladesalir 3 жыл бұрын
@@processminingforpython1934 I am integrating PM4Py into MicroStrategy. Much more easy since it has a full stack of REST API capabilities. I would be more than glad to share the results.
@processminingforpython1934
@processminingforpython1934 3 жыл бұрын
@@ladesalir Yes; we would be definitely interested to see the result!
@nkwachiabel5092
@nkwachiabel5092 2 жыл бұрын
Hi Baha, I have been able to integrate Graphviz visualisations in Power BI Desktop using the python scripting module and I was able to do other things such as filtering, etc. I think it is possible with PM4Py since it is also using Graphviz. I have not tried it yet with PM4Py though. The hack is to do the visualisation in the background, and render it as an image using matplotlib in Power BI Desktop. However, the performance time on Power BI Desktop will vary depending on your dataframe. Let me know if you need further information. Happy to help.
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