Ten Mistakes to Avoid When Creating a Recommendation System « Machine Learning Times – The Machine Learning Times

npressfetimg-1580.png
Originally published in Medium.com, July 27, 2022. 

We’ve been long working on improving the user experience in UGC products with machine learning. Here are our ten key lessons of implementing recommendation systems in business to build a really good product.

1. Define a Goal that Really Contributes to the Business Tasks

The global task of the recommendation system is to select a shortlist of content from a large catalog that is most suitable for a particular user. The content itself can be different — from products in the online store and articles to banking services. FunCorp product team works with the most interesting kind of content — we recommend memes.

To do this, we rely on the history of the user’s interaction with the service. But “good recommendations” from a user perspective and from a business perspective are not always the same thing. For example, we found that increasing the number of likes that a user clicks thanks to more accurate recommendations does not affect retention, a metric that is important for our business. So we started focusing on models that optimize time spent in the app instead of likes.

To continue reading this article, click here.

Source: https://www.predictiveanalyticsworld.com/machinelearningtimes/ten-mistakes-to-avoid-when-creating-a-recommendation-system/12718/

npressfetimg-1204.png
Machine learning

Machine learning models development for shear strength prediction of reinforced concrete beam: a comparative study … – Nature.com

Siddika, A., Al Mamun, M. A., Alyousef, R. & Amran, Y. H. M. Strengthening of reinforced concrete beams by using fiber-reinforced polymer composites: A review. J. Build. Eng. 25, 100798 (2019).

Google Scholar 

<p class="c-article-references__text" …….

Read More
npressfetimg-1131.png
Machine learning

Organic reaction mechanism classification using machine learning – Nature.com

Simonetti, M., Cannas, D. M., Just-Baringo, X., Vitorica-Yrezabal, I. J. & Larrosa, I. Cyclometallated ruthenium catalyst enables late-stage directed arylation of pharmaceuticals. Nat. Chem. 10, 724–731 (2018).

Article 
CAS 

Google Scholar 
…….

Read More
npressfetimg-1058.png
Machine learning

Generative AI: how will the new era of machine learning affect you? – Financial Times

Copyright The Financial Times Limited 2023. All rights reserved.

Follow the topics in this article

Markets data delayed by at least 15 minutes. © THE FINANCIAL TIMES LTD 2023. FT and ‘Financial Times’ are trademarks of The Financial Times Ltd.The Financial Times and its journalism are subject to a self-regulation regime under the FT Editoria…….

Read More