Synthetic time series generation





Artificial neural networks rely heavily on large sets of data to train their models. However, with the constantly evolving data privacy regulations around the world, obtaining high-quality data becomes increasingly challenging, mainly due to security or privacy reasons. Read more and find out how to generate synthetic time series for you machine learning models.
Synthetic time series generator

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Web-gui for Python logs





Logging can help you better understand the flow of a program and discover undesirable behaviour, which you might not even consider while developing. Logs give you information about scenarios that an application is going through. You can label this information according to its importance: debug, info, warning and errors. Logs can provide more insights than a stack trace by telling you what the program state was before it arrived at the line of code where the error occurred.

Logs browser in Flask
Logs browser in Flask

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Migration from Tkinter to Flask

The most popular library to create GUI in Python is Tkinter, which is a part of standard Python installation. Tkinter is a mature and stable tool, widely ported and relatively easy to learn. However, it is also quite old with many drawbacks, among them, it has a limited set of widgets. Although the simplistic model is easy to learn, Tkinter also becomes cumbersome with more complex interfaces. Above all, it does not support mobile and web application development.

Tkinter window
Tkinter window

Flask GUI
Flask GUI

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