Author: Brian Keng

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Announcement: Data Science Seminars

At Rubikloud we're big fans of learning (and not just the machine kind)! Since our company revolves around all things data, we've organized a seminar series about just that: data science. Its purpose is to encourage anyone and everyone to learn more about data and how to use it. These seminars are open to the whole company and cover topics...

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Beyond Collaborative Filtering (Part 2)

Note: This is Part 2 of our series on recommendation systems and collaborative filtering. Please check out Part 1 of our series for the challenges of building a retail specific product recommendation system and an overview of collaborative filtering. Retail Product Recommendations Once a good collaborative filtering model has been built using matrix factorization, the individual dense latent customer and product vectors can...

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Beyond Collaborative Filtering (Part 1)

Here at Rubikloud, a big focus of our data science team is empowering retailers in delivering personalized one-to-one communications with their customers. A big aspect of personalization is recommending products and services that are tailored to a customer's wants and needs. Naturally, recommendation systems are an active research area in machine learning with practical large scale deployments from companies such...

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