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whylogs download for Windows

Free download whylogs Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named whylogs whose latest release can be downloaded as v1.3.10sourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named whylogs with OnWorks for free.

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- 1. Downloaded this application in your PC.

- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 3. Upload this application in such filemanager.

- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.

- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

SCREENSHOTS

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whylogs


DESCRIPTION

whylogs is an open-source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (called whylogs profiles) which they can use to track changes in their dataset Create data constraints to know whether their data looks the way it should. Quickly visualize key summary statistics about their datasets. whylogs profiles are the core of the whylogs library. They capture key statistical properties of data, such as the distribution (far beyond simple mean, median, and standard deviation measures), the number of missing values, and a wide range of configurable custom metrics. By capturing these summary statistics, we are able to accurately represent the data and enable all of the use cases described in the introduction.



Features

  • Detect data drift in model input features
  • Detect training-serving skew, concept drift, and model performance degradation
  • Validate data quality in model inputs or in a data pipeline
  • Perform exploratory data analysis of massive datasets
  • Track data distributions & data quality for ML experiments
  • Enable data auditing and governance across the organization


Programming Language

Python


Categories

Data Pipeline

This is an application that can also be fetched from https://sourceforge.net/projects/whylogs.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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