{"id":295,"date":"2020-04-24T06:06:20","date_gmt":"2020-04-24T06:06:20","guid":{"rendered":"https:\/\/recommender-systems.com\/?page_id=295"},"modified":"2021-01-21T17:24:07","modified_gmt":"2021-01-21T16:24:07","slug":"resources","status":"publish","type":"page","link":"https:\/\/recommender-systems.com\/resources\/","title":{"rendered":"Resources"},"content":{"rendered":"\n

Recommender-System Software Libraries & APIs<\/h3>
There is a plethora of software libraries and APIs that often implement dozens of recommendation algorithms. In the Google Sheet below, you find a collection of recommender-system libraries and APIs (early draft \/ work-in-progress!). If you would like to add or change information, please send a request and provide us with some details about yourself....<\/div>

Read more ...<\/a><\/p><\/div>

List of RecSys Researchers<\/h3>
The Google Map below shows experts in the field of recommender systems. Our goal is to keep this map up-to-date with senior and active recommender-systems researchers. The map provides a good starting point for prospective Ph.D. students looking for potential supervisors; organizations and businesses looking for recommender-systems experts for joint projects or consultancy jobs, and...<\/div>

Read more ...<\/a><\/p><\/div>

Datasets<\/h3>
There are a plethora of recommender-system datasets, and, more generally, almost every machine learning dataset can be used for recommendation systems, too. The de-facto standard dataset for recommendations is probably the MovieLens dataset (which exists in multiple variations). Based on a small study that we conducted, 40% of all research papers at the ACM Recommender...<\/div>

Read more ...<\/a><\/p><\/div>

Computing Resources<\/h3>
Running recommender-system experiments may require significant computing resources. Especially memory-based approaches like kNN might need more memory than a normal desktop computer offers. Luckily, many organisations offer free or cheap (cloud) computing resources, though often limited in their free versions Cloud GPUs https:\/\/vast.ai\/ claims to reduce GPU costs by factor 3-5 as they don\u00b4t offer...<\/div>

Read more ...<\/a><\/p><\/div>

Competitions, Challenges, Shared Tasks & Living Labs<\/h3>
To test your skills in recommender-system development and research, competitions, shared tasks, and living labs are ideal. Notable initiatives include Kaggle is the major platform for machine learning competitions, which includes many recommender-systems competitions. The ACM RecSys Challenge is co-hosted every year alongside the ACM RecSys conference. It is sponsored by major industry partners who...<\/div>

Read more ...<\/a><\/p><\/div>

Recommendations-As-a-Service (RaaS)<\/h3>
While recommender-system software libraries and APIs support you in developing a recommender system, a Recommender-System As-a-Service (RaaS) does all the work for you. Typically, you can integrate a recommender system into e.g. your e-commerce website or blog with a few clicks or lines of code. A RaaS comes with some compromises relating to flexibility, control...<\/div>

Read more ...<\/a><\/p><\/div>

Prizes & Awards<\/h3>
NVIDIA Team wins the ACM RecSys Challenge 2020 It seems that NVIDIA becomes a new big player in the recommender-system community. After introducing Merlin – a Framework for Deep Recommender Systems – and offering an online course for Building Intelligent Recommender Systems, a team of NVIDIA employees now won the ACM RecSys Challenge 2020. The...<\/div>

Read more ...<\/a><\/p><\/div>

https:\/\/Your-Project.Recommender-Systems.com<\/h3>
If you have a project related to recommender systems, we would be glad to support you with web space and a sub-domain like https:\/\/Your-Project.Recommender-Systems.com. Alternatively, you may get only a subdomain that forwards to your website at some other website host (e.g. GitHub or GoDaddy). If you are interested, please contact us, and let us...<\/div>

Read more ...<\/a><\/p><\/div><\/div>\n

\r\n
\r\n \r\n <\/i>\r\n <\/a>\r\n <\/span>\r\n<\/div>
\r\n \r\n <\/i>\r\n <\/a>\r\n <\/span>\r\n<\/div><\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-295","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/pages\/295","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/comments?post=295"}],"version-history":[{"count":7,"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/pages\/295\/revisions"}],"predecessor-version":[{"id":1659,"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/pages\/295\/revisions\/1659"}],"wp:attachment":[{"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/media?parent=295"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/categories?post=295"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/recommender-systems.com\/wp-json\/wp\/v2\/tags?post=295"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}