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Filltron

inden FastScript

(1 bedømmelser)

Make predictions or fill missing values with machine learning. Powered by TensorFlow.js.

Make machine learning powered predictions from the safety and comfort of your own spreadsheet.

Autofill missing values with neural networks.

Powered by TensorFlow.js.

This tool operates on a spreadsheet table. One column is identified as the output/prediction column, and the others are treated as inputs to the machine learning model. All columns should contain numbers or label text (e.g., true/false, English/French/German, mystery/fantasy/memoir).

This tool will generate a machine learning model (composed of a number of dense and embedding layers) for the data, and will begin training the model. After each epoch (round of training), values that were initially missing will be generated. As the training progresses, values will (in general) become more accurate.

Getting started:

  • Launch the add-in by clicking the Filltron button from the Home tab ribbon.
  • Set the table address in the taskpane display. You may either enter the address in A1 style, or simply select your full table then click "Use active selection".
  • Toggle the checkbox depending on whether the table you have defined includes header labels.
  • Select the column that will contain the output/prediction values. This column should contain values in some cells (in order to train your data) but not in all cells (the empty cells will contain the predictions).
  • Click the start button to begin the process. Progress will be tracked below the start button. You can click the "Stop/Start Over" button at any time to stop the process. Any prediction values that have already been generated will remain in your spreadsheet. Generated values are highlighted in light blue.

Appfunktioner

Når denne app bruges,
  • Kan læse og foretage ændringer i dit dokument
  • Kan sende data via internettet

Overblik

https://store-images.s-microsoft.com/image/apps.23155.19495796-9537-4e45-b279-cf597d989905.08318191-be0a-42b1-ba60-d5622091a347.bac10ffe-2fdb-431d-837e-58b8620f4c4d.png
Dansk (Danmark)
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