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TextBuddy for macOS VS Evidently AI

Compare TextBuddy for macOS VS Evidently AI and see what are their differences

TextBuddy for macOS logo TextBuddy for macOS

A Swiss Army knife for plain text.

Evidently AI logo Evidently AI

Open-source monitoring for machine learning models
  • TextBuddy for macOS Landing page
    Landing page //
    2022-02-17
  • Evidently AI Landing page
    Landing page //
    2023-08-19

TextBuddy for macOS videos

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Evidently AI videos

How to Monitor Machine Learning Models (Evidently AI)

Category Popularity

0-100% (relative to TextBuddy for macOS and Evidently AI)
Text Editors
100 100%
0% 0
AI
0 0%
100% 100
Productivity
100 100%
0% 0
Developer Tools
13 13%
87% 87

User comments

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Social recommendations and mentions

Evidently AI might be a bit more popular than TextBuddy for macOS. We know about 2 links to it since March 2021 and only 2 links to TextBuddy for macOS. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

TextBuddy for macOS mentions (2)

  • Alternative to WordService?
    I use TextBuddy for those purposes https://textbuddy.app/. Source: almost 3 years ago
  • Image OCR into Markdown
    TextBuddy can OCR, but not sure about handwritten: https://textbuddy.app. It's a great little plaintext companion app. Source: about 3 years ago

Evidently AI mentions (2)

  • [D] Using MLFlow for model performance tracking
    It is doable. However the main focus of MLFlow is in experiment tracking. I would suggest for you to look into another monitoring tools such evidentlyai . You can track more things than performance (e.g.data drift). Which may be helpful in a production setting. Source: almost 2 years ago
  • Five Data Quality Tools You Should Know
    Evidently is an open-source Python library that analyzes and monitors machine learning models. It generates interactive reports based on Panda DataFrames and CSV files for troubleshooting models and checking data integrity. These reports show model health, data drift, target drift, data integrity, feature analysis, and performance by segment. - Source: dev.to / over 2 years ago

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