talk · HACKER NEWS RECOMMENDATION
Bay Area Vision Meeting: Unsupervised Feature Learning and Deep Learning
Google TechTalks · 9 HN recommenders · 7 recommendation months
Recommended by 9 Hacker News commenters across 7 months (2011–2013).
SignalTube analysis
Among 37 other talk videos tagged Machine learning & deep learning, the mean is 2.6 distinct HN recommenders. This video has 9 distinct HN recommenders, about 3.5× that mean. Recommendations span 7 distinct months, longer than the peer average of 2.4 months. This is a data-derived comparison, not a human review or quality rating.
82% of its 11 labeled comments are marked as recommendations or strong recommendations. HN mention years are 2011–2013; those years describe discussion history, not upload date. Its verified runtime is 48 minutes 10 seconds. YouTube lists its publication date as 2011-04-11.
- Channel / speaker
- Google TechTalks
- Verified runtime
- 48m 10s
- YouTube upload date
- 2011-04-11
- Hacker News mention years
- 2011–2013
SAME TOPIC AND FORMAT
Compare with related videos
The comparison cohort uses other talk videos in Machine learning & deep learning. “Shared recommenders” counts HN users who recommended both videos in the source graph.
| Video | HN recommenders | Recommendation months | Positive label share | Shared recommenders | Runtime | Upload date |
|---|---|---|---|---|---|---|
| Bay Area Vision Meeting: Unsupervised Feature Learning and Deep LearningCurrent video | 9 | 7 | 82% | — | 48m 10s | 2011-04-11 |
| USENIX Security '18-Q: Why Do Keynote Speakers Keep Suggesting That Improving Security Is Possible?talk · USENIX | 10 | 10 | 50% | No recorded overlap | 51m 22s | 2018-08-16 |
| [1hr Talk] Intro to Large Language Modelstalk · Andrej Karpathy | 9 | 6 | 45% | No recorded overlap | 59m 48s | 2023-11-23 |
| Brains, Sex, and Machine Learningtalk · Google TechTalks | 7 | 5 | 58% | 2 (22%) | 60m 19s | 2012-08-17 |
THREE SOURCE-BASED CONTEXT POINTS
Why Hacker News recommends it
Each note combines the dataset’s stance label and short rationale; comment bodies are not reproduced. Open the HN source for the original discussion.
The archive classifies this as a strong recommendation in “Neural Network Visualisation in Clojure”. Its short rationale: Visualizes hierarchy of features learned by successive deep net layers.
The archive classifies this as a strong recommendation in “Scientists See Promise in Deep-Learning Programs”. Its short rationale: Most useful overview of unsupervised feature learning.
The archive classifies this as a contextual reference in “Darpa Has Seen the Future of Computing ... And It's Analog”. Its short rationale: Example of breakthroughs in neural networks for pattern recognition.