v0.5.0 NLP metrics and Auto Segmentation Release

whylogs release v0.5.0

Hi everyone! We’ve now released whylogs v0.5.0 🚀. whylogs is an open standard for data and ML logging created by WhyLabs. 👩🏽‍🔬

This release includes:
📝 Support for tracking NLP metrics such as Word Error Rate (WER), Match Error Rate (MER), Word Information Lost (WIL)
𝌋 Auto segmentation to help you discover meaningful segments in your dataset. Save segments for future use so that you can create separate profiles for each segment as data is streamed during deployment or training. Compare segments to help identify bias, and so much more!
🐛 Various Bug fixes.
📚 Documentation updates: Full documentation can be found at https://docs.whylabs.ai or Github https://github.com/whylabs/whylogs
📈 You can push your whylogs profiles directly to WhyLabs Platform for monitoring if you have an API key. Need an API key? Sign up for the free account here: https://bit.ly/whylabs-free-sign-up
❤️ Give us feedback or chat with our team on Slack: http://join.slack.whylabs.ai/

Below is the detailed change log:

✨ Features

• API and method to auto segment features in a model. #255 [@bernease, @lalmei]
• NLP metrics such as Word Error Rate #248 [@lalmei]

🐛 Bug Fixes

• Fix non-tracked character positions in String Tracker merge#257 [@lalmei]
• Fix number of tokens in StringTracker merge #256 [@lalmei]
• Add example showing custom tokenizer for string tracking #253 [@lalmei]

📚 Documentation

• Add String Tracker Notebook example link in README #252 [@lalmei]
• Add example showing custom tokenizer for string tracking #253 [@lalmei]
• update release draft to use correct version number #249 [@lalmei]

🔨 Maintenance

• Refactor datasetprofile's flatten profile #250 [@lalmei]
• Fix make bump-x scripts #258 [@lalmei ]