brianjkim21

5 ms·

1. 1.▲
   by brianjkim21 2y ago

   this is sick, thanks for sharing
2. 2.▲
   by brianjkim21 2y ago

   thanks roanak!
3. 3.▲
   by brianjkim21 2y ago

   PMs and Execs are pushing devs to do docs classification and extract data from text ("see I can do it on chatGPT!") so they're using Taylor (trytaylor.ai) to build production grade text pipelines ;) In all seriousness, custom
4. 4.▲
   Ask HN: How do you track the accuracy of your text classifications over time?

   1 points by brianjkim21 2y ago|0 comments
5. 5.▲
   by brianjkim21 2y ago

   thanks :) you too!
6. 6.▲
   by brianjkim21 2y ago

   thanks! primarily classical. we designed an ensemble that considers both lexical & semantic similarity and trained on large datasets of labeled text. we train our own 'out-of-the-box' models (like the intent classification, IA
7. 7.▲
   Content classification based on IAB taxonomy(trytaylor.ai)

   4 points by brianjkim21 2y ago|5 comments
8. 8.▲
   Show HN: Text classifiers (just bring your labels; no training data needed)(trytaylor.ai)

   1 points by brianjkim21 2y ago|0 comments
9. 9.▲
   Configurable Text Classification for Devs(trytaylor.ai)

   2 points by brianjkim21 2y ago|0 comments
10. 10.▲
    Passing developer params to text classification models [video](youtube.com)

    2 points by brianjkim21 2y ago|0 comments
11. 11.▲
    O*Net Occupation Code Labeler(trytaylor.ai)

    1 points by brianjkim21 2y ago|0 comments
12. 12.▲
    Custom text classification models for devs(trytaylor.ai)

    2 points by brianjkim21 2y ago|0 comments
13. 13.▲
    by brianjkim21 2y ago

    Example? To clarify, I'm referring to product eng and SWEs. If you have a Data / ML team, they will handle ofc.
14. 14.▲
    Ask HN: Are engineers afraid of free text?

    4 points by brianjkim21 2y ago|3 comments
15. 15.▲
    by brianjkim21 3y ago

    thanks. yup, it's on our roadmap :)
16. 16.▲
    by brianjkim21 3y ago

    yup, we designed an ensemble that considers both lexical & semantic similarity and trained on large datasets of labeled text. also building data pipelines to prevent models going stale. max 20 docs per request for free api. no official
17. 17.▲
    by brianjkim21 3y ago

    appreciate the feedback. will update, thanks.
18. 18.▲
    Show HN: Out-of-the-box text classification models(ycombinator.com)

    20 points by brianjkim21 3y ago|10 comments
19. 19.▲
    Show HN: Label text data into 16 topic buckets(loom.com)

    1 points by brianjkim21 3y ago|0 comments
20. 20.▲
    Show HN: Classify user queries with 1k topic labels – no signup req'd(trytaylor.ai)

    2 points by brianjkim21 3y ago|0 comments
21. 21.▲
    Show HN: Query your unstructured text with SQL [video](youtube.com)

    4 points by brianjkim21 3y ago|0 comments
22. 22.▲
    Show HN: Sonar – Auto Generated Data Catalog(trytaylor.ai)

    2 points by brianjkim21 3y ago|0 comments