Qt Contributors Summit 2019 Program/Qt Machine Learning and Math: Difference between revisions
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(Created page with "=== Introduction === * Slides: * The Python modules that are used in ML have C++ implementations under the hood. Here are some examples: * TensorFLow * Keras * Scikit-...") |
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* Slides: | * Slides: | ||
* The Python modules that are used in ML have C++ implementations under the hood. Here are some examples: | * 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: | * 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; | * Data science work consists in Data Extracting, transforming it, loading it and cleaning it, and just then they apply ML techniques; | ||
* Math in C++: | * 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 === | === Thoughts on how Qt and Qt for Python fit in this market === | ||
* Make the interface interaction with Qt and these libraries | * 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; | * PyTorch offers some support that'd make it easy to integrate with Qt; | ||
* Create training interfaces [...]; | * Create training interfaces [...]; | ||
* Show insides of a module like TensorFlow it's doing in its website; | * 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; | * 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; | * 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; | * 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; | |||
Revision as of 14:11, 21 November 2019
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;
- We could provide building blocks to people to build their own dashboard;