[PyTorch] Porting Chapter Recommender Systems

[AnirudhDagar]

Currently, the only missing chapter in the PyTorch port of the book is Recommender Systems. Given the number of requests that we have been receiving regarding this section, and rising interest among readers, this is a good time to add PyTorch support.

This Issue serves as a tracker for various sections that need to be added. If you're interested in working on this issue, please comment below with "I'm working on <section X>, <section Y>, etc..." so that others don't pick the same sections as you do. Please do not pick more than two sections at once. You are free to send a PR and then pick other sections as well.

We need to complete the sections in order. Before picking a section, make sure the previous sections are already implemented (since the latter sections use functions saved in the earlier sections of the chapter), if not you should start with picking that previous section and implement that first. Thanks!!

• 16.1. Overview of Recommender Systems (recsys-intro.md)
• 16.2. The MovieLens Dataset (movielens.md) -> [PyTorch] Add The MovieLens Dataset #2030
• 16.3. Matrix Factorization (mf.md) -> [Pytorch] Add Pytorch port for 16.3. Matrix Factorization #2031
• 16.4. AutoRec: Rating Prediction with Autoencoders (autorec.md)
• 16.5. Personalized Ranking for Recommender Systems (ranking.md)
• 16.6. Neural Collaborative Filtering for Personalized Ranking (neumf.md)
• 16.7. Sequence-Aware Recommender Systems (seqrec.md)
• 16.8. Feature-Rich Recommender Systems (ctr.md)
• 16.9. Factorization Machines (fm.md)
• 16.10. Deep Factorization Machines (deepfm.md)

Please go through CONTRIBUTING.md to understand the d2l development process and how to setup your dev environment. Feel free to raise your doubts/questions here or tag someone from the team.

cc @astonzhang
@divo12 @KuanHaoHuang I believe you're interested in this too :)

[KuanHaoHuang]

Thanks Anirudh, for starting and arranging this tracker issue.

I'm working on 16.2. The MovieLens Dataset (#2030).

[shanmo]

I'm working on 16.3. Matrix Factorization, finished in this PR #2031

[divo12]

I'll be working on 16.5 Personalized Ranking for Recommender Systems

[KuanHaoHuang]

I'm working on 16.4. AutoRec: Rating Prediction with Autoencoders

[AnirudhDagar]

Thanks a tonne @KuanHaoHuang @shanmo @divo12. I'll review the PRs this week.

[KuanHaoHuang]

Hi @AnirudhDagar, is there anything we can do to help this issue to progress?

[FanwangM]

Are there any updates on this issue? It is noticed that many sections are missing in Chapter 16. Thanks for helping with this nice book, which is really helpful!

[ENate]

Hi Team. I will like to contribute to these topics. I just noticed that these were requested like 1+ year ago. Are there any available topics? Thanks.