There are a few sources on the Web where you find great collections of datasets, code, and advice. Some of them are listed here, let us know if something is missing.
A nice and relatively recent collection of recommender-system tools and best practice guidelines maintained by different persons at Microsoft. To the best of our knowledge, the collection was first introduced at the ACM RecSys Conference 2019  by Graham et al., and later presented at the Web Conference 2020 by three different authors, i.e. Argyriou et al. .
 S. Graham, J.-K. Min, and T. Wu, “Microsoft recommenders: tools to accelerate developing recommender systems
,” in Proceedings of the 13th ACM Conference on Recommender Systems
, 2019, pp. 542–543.
 A. Argyriou, M. González-Fierro, and L. Zhang, “Microsoft Recommenders: Best Practices for Production-Ready Recommendation Systems
,” in Companion Proceedings of the Web Conference 2020
, 2020, pp. 50–51.
RecSysWiki is a Wikipedia-like website to which everyone can contribute. The wiki was founded in 2011 by Alan Said and had a long downtime between April 2018 and late 2020.
News Relating to Wikis and Curated Collections
After a bit more than 2 years of downtime, RecSys Wiki is back online. RecSys Wiki was established in 2011 by Alan Said (and others?) but went offline in 2018. It is great to see this Wiki be online again.
Here is a curated collection of my favourite posts for people starting out in recommender systems and personalization. This was created in preparation for our summer interns in the recommendations team at Flipboard! https://flipboard.com/@arnie0426/building-recommender-systems-nvue3iqtgrn10t45