Stanford CS330: Deep Multi-task and Meta Learning | Autumn 2020

Total watch time

18h 26m

at 1× speed · exactly 18 hours, 25 minutes, 38 seconds at 1×

custom

1×	18h 25m 38s
1.25×	14h 44m 30s
1.5×	12h 17m 5s
1.75×	10h 31m 47s
2×	9h 12m 49s

Average video1h 18m 58s

Longest1h 27m 41s

Shortest42m 26s

Compare Open on YouTube JSON

Plan to finish

About 19 days at an hour a day

Pick a daily pace and the days you'll watch. Ticked videos are skipped.

At one hour a day, every day, this playlist takes about 19 days. Turn on JavaScript to plan around your week.

Videos (14)

18h 26m in total · tick what you've watched

Tick videos you've watched — progress is saved in this browser.


1	Stanford CS330: Deep Multi-task and Meta Learning \| 2020 \| Lecture 1 - Intro to Multi-Task Learning	42:26	2022-01-28
2	Stanford CS330: Deep Multi-task and Meta Learning \| 2020 \| Lecture 2 - Multi-Task Learning	1:18:25	2022-01-28
3	Stanford CS330: Deep Multi-task & Meta Learning \| 2020 \| Lecture 3 - Transfer & Meta-Learning	1:17:38	2022-01-28
4	Stanford CS330: Deep Multi-task and Meta Learning \| 2020 \| Lecture 4 - Optimization Meta-Learning	1:17:09	2022-01-28
5	Stanford CS330: Deep Multi-task & Meta Learning \| 2020 \| Lecture 6: Non-Parametric Few-Shot Learning	1:24:18	2022-01-28
6	Stanford CS330: Deep Multi-task and Meta Learning \| 2020 \| Lecture 7 - Advanced Meta-Learning Topics	1:27:41	2022-01-28
7	Stanford CS330: Deep Multi-task and Meta Learning \| 2020 \| Lecture 8 - Bayesian Meta-Learning	1:26:18	2022-02-01
8	Stanford CS330: Deep Multi-task and Meta Learning \| 2020 \| Lecture 9 - Meta Reinforcement Learning	1:21:44	2022-02-01
9	Stanford CS330:Multi-task and Meta Learning \| 2020 \| Lecture 10 - Model-Based Reinforcement Learning	1:24:39	2022-02-01
10	Stanford CS330:Multi-task and Meta Learning \| 2020 \| Lecture 11:Meta RL: Adaptable Models & Policies	1:17:29	2022-02-01
11	Stanford CS330: Deep Multi-task and Meta Learning \| 2020 \| Lecture 13: A Graphical Model Perspective	1:18:45	2022-02-01
12	Stanford CS330:Multi-task and Meta Learning \| 2020 \| Lecture 14: Hierarchical RL and Skill Discovery	1:25:00	2022-02-01
13	Stanford CS330: Deep Multi-task and Meta Learning \| 2020 \| Lecture 15 - Lifelong Learning	1:24:21	2022-02-01
14	Stanford CS330: Deep Multi-task and Meta Learning \| 2020 \| Lecture 17: Frontiers and Open-Challenges	1:19:45	2022-02-01

Embed a badge

Show the watch time in a README or course description — it links back here and updates itself

Markdown

[![Watch time: 18h 26m · 14 videos](https://playlistduration.com/badge/playlist/PLoROMvodv4rOxuwpC_raecBCd5Jf54lEa.svg)](https://playlistduration.com/playlist/PLoROMvodv4rOxuwpC_raecBCd5Jf54lEa)

HTML

<a href="https://playlistduration.com/playlist/PLoROMvodv4rOxuwpC_raecBCd5Jf54lEa"><img src="https://playlistduration.com/badge/playlist/PLoROMvodv4rOxuwpC_raecBCd5Jf54lEa.svg" alt="Watch time: 18h 26m · 14 videos" width="210" height="20"></a>

Add ?speed=1.5 to the image URL for the time at that speed, ?label=Course to change the left text, or ?style=flat-square for square corners.

Want the numbers themselves? GET https://playlistduration.com/api/v1/playlist/PLoROMvodv4rOxuwpC_raecBCd5Jf54lEa returns them as JSON — free, no key. API docs →

Data from the YouTube Data API as of 2026-09-22 (cached). Private or deleted videos are excluded from totals.