Kaggle

@kaggle · San Francisco · joined 06 Oct 2009

Kaggle is the largest global AI community of developers, researchers, and enthusiasts who compete, collaborate, and benchmark what's next in AI.

319 157Followers

292Following

5 686Posts total

76.3KViews on collected posts

Against accounts of the same size

11 posts from the last 90 days, next to the 100K–1M follower range. below its peers on both reach and engagement.

Median views3 749this account4 404median for 100K–1M

Reach, %1.17%this account1.84%median for 100K–1M

Engagement, %0.84%this account1.47%median for 100K–1M

Metric	This account	Median for 100K–1M	Ratio
Median views per post	3 749	4 404	0.85×
Reach (views ÷ followers)	1.17%	1.84%	0.64×
Engagement rate	0.84%	1.47%	0.57×

Others in this range → Compare with another account → How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

11.6K19 Aug

18.6K20 Aug

262

205

3.7K21 Aug

17K28 Aug

591

5729 Aug

12.6K

11.6K4 Sep

Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.49%19 Aug

0.84%20 Aug

0.38%

0.49%

0.53%21 Aug

0.62%28 Aug

1.69%

5.26%29 Aug

0.89%

3.90%

1.08%4 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.47%.

What the audience does

Likes66.7%477 in total

Reposts6.9%49 in total

Replies7.7%55 in total

Quotes1.8%13 in total

Bookmarks16.9%121 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

Followers by day

5 Sep

Daily snapshots since 05 Sep 2026; the dashed line is the starting count.

Latest posts

Introducing ExtractBench on Kaggle Benchmarks with @llama_index. When AI agents rely on schema-guided extraction before human review, one truncated schedule or invented value becomes a wrong payment or decision. ExtractBench evaluates models in workflows based on real-world htt 11.6K views · 108 likes · 11 reposts · 4 replies 04 Sep 2026 @kaggle I learn that poor people died first in the titanic 77 views · 3 likes · 0 reposts · 0 replies 29 Aug 2026 Ready to build models that support knee MRI interpretation? 🩻🦵 Check out this starter notebook by Pilkwang Kim. It is a great starting point to read the DICOM acquisitions, sample and normalise the MRI slices, and turn a pretrained vision backbone into twelve abnormality 12.6K views · 87 likes · 21 reposts · 2 replies 29 Aug 2026 @kaggle xgboost 57 views · 3 likes · 0 reposts · 0 replies 29 Aug 2026 @kaggle XGBoost 591 views · 10 likes · 0 reposts · 0 replies 28 Aug 2026 What's one thing you learned on Kaggle? 🌟 17K views · 73 likes · 1 reposts · 26 replies 28 Aug 2026 @kaggle @GertLabs nice 3.7K views · 19 likes · 0 reposts · 1 replies 21 Aug 2026 @kaggle @GertLabs do the agents get any signal from the caller's voice or is it purely the conversation text? 205 views · 0 likes · 0 reposts · 1 replies 20 Aug 2026 @kaggle @GertLabs a tie for first between claude and gemini, so the real winner is whoever's caller was most polite about being an identity thief 262 views · 1 likes · 0 reposts · 0 replies 20 Aug 2026 Today, we’re excited to launch Adversarial Customer Service on Kaggle Benchmarks, in partnership with @GertLabs. This benchmark is a two-sided security game: one model plays a bank's support agent holding customer records and a verification policy, the other plays a caller who h 18.6K views · 131 likes · 15 reposts · 7 replies 20 Aug 2026 I knew I belonged on Kaggle when... (finish the sentence) 👇 11.6K views · 42 likes · 1 reposts · 14 replies 19 Aug 2026