#InterpretableML

Live, measured metrics for the hashtag #InterpretableML from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.

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0
Uses / 7 days
Mastodon
0
Accounts / 7 days
Mastodon
7
Recent posts
Mastodon
~0/hr
Recent pace
Mastodon · last 7
0.3
Avg reactions / post
Mastodon · last 7

Day-by-day usage

measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 11:13 UTC
0
07-21
0
07-22
0
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0
07-24
0
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07-27

0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.

Related hashtags

measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 11:13 UTC

No related tags with measured usage found for #interpretableml.

Live pulse

measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 11:13 UTC

Everything below is measured over the latest 7 public posts (spanning ~15355 hours).

Posting hours (UTC)

00:0012:0023:00

Languages: English (7)

Avg boosts / post: 1.3

Top of the latest posts

  • This book is golden! (and I think I'll have to read it again because it's so full of information!) For anyone trying to understand their models, Serg Masís' book "Interpretable Machine Learning with #Python" provides the right mix of theory

    Cosima Meyer@[email protected]♥ 2↻ 42024-10-01 06:00 UTCView post →

  • Interested in interpretable ML, particularly for LLMs? eg "causal" interpretability, as in the "OthelloGPT" paper [1]? Let's connect! 1. https://arxiv.org/abs/2210.13382 #ai #machinelearning #interpretability #interpretableml #mechanisticin

    Marco 🌳 Zocca@[email protected]♥ 0↻ 02024-10-12 06:28 UTCView post →

  • And while this is true for any modeling approach, I think it's especially relevant as we move to more complex models. In my experience, interpretability is important not only in making models accessible to the end user but also in the devel

    Cosima Meyer@[email protected]♥ 0↻ 12024-10-01 06:00 UTCView post →

Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/interpretableml