MIT 6.S094: Convolutional Neural Networks for End-to-End Learning of the Driving Task
Published January 25, 2017
At a glance
Views
245,683
Likes
2,921
Comments
116
Performance vs. channel
All-time outlier score
Engagement rate
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About
This is lecture 3 of course 6.S094: Deep Learning for Self-Driving Cars taught in Winter 2017. This lecture introduces computer vision, convolutional neural networks, and end-to-end learning of the driving task. INFO: Slides: http://bit.ly/2HdXYvf Website: https://deeplearning.mit.edu GitHub: https://github.com/lexfri…
- Published
- January 25, 2017
- Made for kids
- No
More features coming
We're working on new analytics and tools. Stay tuned.
How MIT 6.S094: Convolutional Neural Networks for End-to-End Learning of the Driving Task is doing
It has 245K views in total. It ranks #9,213,793 among tracked YouTube videos by views.
Key facts about MIT 6.S094: Convolutional Neural Networks for End-to-End Learning of the Driving Task
- Total views
- 245K
- Total likes
- 2.92K
- Total comments
- 116
- Published
- January 25, 2017
- Global rank by views
- #9,213,793
Frequently asked questions
How many views does MIT 6.S094: Convolutional Neural Networks for End-to-End Learning of the Driving Task have?
MIT 6.S094: Convolutional Neural Networks for End-to-End Learning of the Driving Task has 245,683 views, 2,921 likes and 116 comments, ranking #9,213,793 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.
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