Topic Modeling using scikit-learn and Non Negative Matrix Factorization (NMF)
Published December 13, 2020
At a glance
Views
10,047
Likes
156
Comments
9
Performance vs. channel
All-time outlier score
Engagement rate
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About
#datascience #machinelearning #ml Link to Topic Modeling using LDA video - https://www.youtube.com/watch?v=25JOEnrz40c Link to playlist containing banking ML use cases - https://www.youtube.com/playlist?list=PL3N9eeOlCrP4uLCtas5vxq09sWz6jJXrw In this video we will see how to build topic model using non negative matri…
- Published
- December 13, 2020
- Made for kids
- No
More features coming
We're working on new analytics and tools. Stay tuned.
How Topic Modeling using scikit-learn and Non Negative Matrix Factorization (NMF) is doing
It has 10.0K views in total. It ranks #13,705,336 among tracked YouTube videos by views.
Key facts about Topic Modeling using scikit-learn and Non Negative Matrix Factorization (NMF)
- Total views
- 10.0K
- Total likes
- 156
- Total comments
- 9
- Published
- December 13, 2020
- Global rank by views
- #13,705,336
Frequently asked questions
How many views does Topic Modeling using scikit-learn and Non Negative Matrix Factorization (NMF) have?
Topic Modeling using scikit-learn and Non Negative Matrix Factorization (NMF) has 10,047 views, 156 likes and 9 comments, ranking #13,705,336 among tracked YouTube videos by views.
How accurate are these YouTube video analytics?
View, like, and comment counts come from YouTube's public API and refresh regularly. Growth and revenue figures are estimates built from tracked historical data, so they can differ slightly from what the creator sees privately in YouTube Studio.
What is the outlier score?
How this video's views compare to the channel's usual Shorts or long-form video. A 2x score means double the usual views for that channel, 0.5x means half.
What is engagement rate and how is it calculated?
Likes and comments per view, compared to this channel's typical engagement rate — shown as above or below what's usual for the channel.
How is the revenue estimate calculated?
It's a rough public estimate based on a $0.7–$2.0 CPM (revenue per 1,000 views) applied to view count — not actual creator earnings, which depend on ad rates, audience geography, and monetization settings YouTube doesn't expose publicly.
Is this YouTube video analytics checker free?
Yes. You get 10 free channel and video analytics lookups per 24 hours without an account — logging in, which is also free, removes that limit entirely.