View source for Qt Contributors Summit 2019 Program/Qt Machine Learning and Math

[[Category:QtCS2019]]
== Introduction ==

* Slides: 
* The Python modules that are used in ML have C++ implementations under the hood. Here are some examples:
** TensorFLow
** Keras
** Scikit-learn
** Theano
** PyTorch

* In DS the main Python modules are:
** NumPy
** Pandas

* Data science work consists in Data Extracting, transforming it, loading it and cleaning it, and just then they apply ML techniques;
* Math in C++:
** cmath
** Armadillo
** We don't have math modules in Qt because it's hard to have something so specific;

== Thoughts on how Qt and Qt for Python fit in this market ==

* Make the interface interaction with Qt and these libraries
** The point is not reimplementing data frames or numpy stuff, we want to add support to it on PySide, having widgets ready to use;

* PyTorch offers some support that'd make it easy to integrate with Qt;
* Create training interfaces [...];
* Show insides of a module like TensorFlow it's doing in its website;
* Important to ask ourselves what are we bringing to the table, because there is a lot of things that are already out there doing a pretty good job;
** It's hard to get in to a market that's already established;

* Offer a tool that allows data scientists to interact with the data and modify it;
* If we had a better graphical display system in Qt it'd be easier to implement this kind of thing. Maybe the answer is to fix QtChart, or maybe the answer is to kill QtChart;
** We could provide building blocks to people to build their own dashboard;
*** It'd help a lot the DS people to visualize their data, helping them cleaning it;