#machinelearning #phd #howto
This video is advice for new PhD students in the field of Machine Learning in 2021 and after. The field has shifted dramatically in the last few years and navigating grad school can be very hard, especially when you're as clueless as I was when I started. The video is a personal recount of my mistakes and what I've learned from them. If you already have several published papers and know what to do, this video is not for you. However, if you are not even sure where to start, how to select a topic, or what goes in a paper, you might benefit from this video, because that's exactly how I felt.
Main Takeaways:
- Select niche topics rather than hype topics
- Write papers that can't be rejected
- Don't be discouraged by bad reviews
- Take reviewing & teaching seriously
- Keep up your focus
- Conferences are for networking
- Internships are great opportunities
- Team up with complementary skills
- Don't work too hard
OUTLINE:
0:00 - Intro & Overview
1:25 - Thesis Topic Selection
4:25 - How To Publish Papers
5:35 - Dealing With Reviewers
6:30 - How To Be A Reviewer
7:40 - Take Teaching Seriously
8:30 - Maintain Focus
10:20 - Navigating Conferences
12:40 - Internships
13:40 - Collaborations
14:55 - Don't Forget To Enjoy
Transcript: https://www.notion.so/Yannic-Kilcher-s-PhD-Survival-Guide-Transcript-c507ab8e963e496fbb185cdfdb8d65ae
Credits to Lanz for editing
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0:00 - Intro & Overview
1:25 - Thesis Topic Selection
4:25 - How To Publish Papers
5:35 - Dealing With Reviewers
6:30 - How To Be A Reviewer
7:40 - Take Teaching Seriously
8:30 - Maintain Focus
10:20 - Navigating Conferences
12:40 - Internships
13:40 - Collaborations
14:55 - Don't Forget To Enjoy
