Rubikloud Labs



The Hard Thing about Machine Learning


Posted in Data Science, Labs
By Brian Keng on August 21, 2017

Much of the buzz around machine learning lately has been around novel applications of deep learning models. They have captured our imagination by anthropomorphizing them, allowing them to dream, play games at superhuman levels , and read x-rays better than physicians. While these deep learning models are incredibly powerful with incredible ingenuity built into them, they are …

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Building A Table Tennis Ranking Model


Posted in Data Science, Labs
By Brian Keng on July 4, 2017

Much of the buzz around machine learning lately has been around novel applications of deep learning models. They have captured our imagination by anthropomorphizing them, allowing them to dream, play games at superhuman levels , and read x-rays better than physicians. While these deep learning models are incredibly powerful with incredible ingenuity built into them, they are …

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Data Science at Rubikloud


Posted in Data Science, Labs
By Brian Keng on April 26, 2017

Over the last three years, Rubikloud has had some tremendous growth going from a team of less than a dozen to a fast-growing venture-backed startup with more than 80 people.  In this short time, we’ve assembled a team of talented engineers, retail experts and, of course, incredibly bright data scientists. With access to huge amounts …

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What makes a good recommender system?


Posted in Data Science, Labs
By Anton Mazhurin on March 15, 2017

“I think you should move to Australia. You will be a lot happier there!”. How do you measure the quality of such a recommendation? In our tongue and cheek example, the basic approach would be to let a recommender system choose a large number of people, say 1,000, whom, from the recommender system’s perspective, will …

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Definition of Done


Posted in Engineering, Labs
By Raheel Govindji on January 23, 2017

At Rubikloud, we focus heavily on shipping well-engineered products that are driven by data science and machine learning. That means we spend a lot of time prototyping and working through very large datasets and iterating over performance and feature considerations. This process requires many teams to work together to achieve a complete and shippable product. …

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Gradient Boosting to the Xtreme – Part I


Posted in Data Science, Labs
By Rob Chin on January 23, 2017

A key element of Rubikloud’s philosophy around software is that machine learning should be embedded into business software, not necessarily to replace human intuition, but rather, to augment and enhance it. The reasons for why we believe that to be true, you can refer to Kerry’s posts here: HOW TO USE MACHINE LEARNING TO FURTHER …

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Gradient Boosting to the Xtreme – Part 2


Posted in Data Science, Labs
By Rob Chin on January 23, 2017

In this second blog post in this series on Extreme Gradient Boosting, we will be focusing on how to solve the immediate issue of overfitting that can occur when we have a single decision tree classifier. Please checkout part 1 which covers in detail the principles of decision tree classifiers and some of the challenges that …

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Rubikloud Data Science Seminars: Advanced PostgreSQL Functions and Operators


Posted in Engineering, Labs
By Byron Fung on October 20, 2016

Announcement: Data Science Seminars


Posted in Labs
By Brian Keng on October 12, 2016

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 …

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Beyond Collaborative Filtering (Part 2)


Posted in Data Science, Labs
By Brian Keng on May 30, 2016

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 …

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Beyond Collaborative Filtering (Part 1)


Posted in Data Science, Labs
By Brian Keng on May 18, 2016

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 …

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9 Questions to Ask Before Kicking off any Big Data Project


Posted in General, Labs
By Kerry Liu on May 13, 2015

What do you get when you combine rebranded analytics systems, a minefield of consultants turned “big data experts,” and insanely expensive “big data servers” that look suspiciously similar to commodity machines? You get: the most complicated space for any business or decision maker to navigate. Frankly as one of the providers of what we feel …

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MongoDB vs Cassandra


Posted in General, Labs
By Laura Leslie on October 15, 2014

On the rare occasion that I walk into the engineer pit I am usually hard-pressed to be acknowledged with more than a grunt, smile and a quick glance away from the computer screens. I get it though, “plugged-in” engineers are focused creatures with little to no tolerance for outside distraction. Recently however, I was surprised …

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Data Science: The Endless Possibilities


Posted in Data Science, Labs
By Laura Leslie on September 5, 2014

With continuing advancements in computational power and the collection and processing of data, the world is seeing new and exciting uses for data analytics. From charitable ventures to “smart” homes, the FIFA World Cup and climate change, the examples are endless. Here are a few of my favorites: Help for distressed teens: Started by Nancy …

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Big Data – Big Questions


Posted in Engineering, Labs
By Laura Leslie on August 5, 2014

With the advancements in civilization and technology, we are now seeing the world’s digital data double almost every three years. This exponential growth is leading to innovations and improved efficiencies across multiple industries. When talking about large amounts of data we hear things like machine learning, deep learning, data mining, data lakes, batch and real-time …

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Inside the mind of a Data Scientist:


Posted in General, Labs
By Laura Leslie on August 1, 2014

  This week, we went around the office and asked all of our engineers and data scientists one question: “What does data science mean to you?”. Stay tuned for that full post next week. One of our data scientists with a specialization in machine learning took the topic home and wrote in an email response. …

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Big Data: To Build Or Not To Build?


Posted in Engineering, Labs
By Dan Theirl on June 18, 2014

Searching the Internet, I was surprised to find a lack of complete build versus buy articles published on big data. There were plenty of technical papers, there were several high level articles on the cost of hardware, but no single research paper that looked at all of the various costs when deciding whether to build …

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The Big Data Balancing Act: Flexibility, Power and Accessibility


Posted in General, Labs
By Kerry Liu on February 7, 2014

With the democratization of data, the winners will be those who deliver actionable insight. In an ideal world, big data means business questions can be answered with facts and observations, rather than guesses and hunches. This is why the democratization of data is seen as the holy grail of data tools. You can make a good case …

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What does SaaS mean in our world?


Posted in General, Labs
By Kerry Liu on January 22, 2014

One of my favorite blogs is (www.saastr.com), which is run by Jason Lemkin, a serial entrepreneur turned VC.  A key part of the blog’s appeal is every post brings us one step closer to understanding what SaaS truly means. People automatically assume SaaS has to be software hosted in someone else’s environment. The notion it …

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Doing the impossible…


Posted in General, Labs
By Dan Theirl on November 28, 2013

“Any sufficiently advanced technology is indistinguishable from magic.” Arthur C. Clark One of my favorite technology quotes. When I stand back and visualize the future of our world I dream of that moment, when technology stops being technology. When technology becomes something greater to our everyday lives. It not only changes the way we do …

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Why would anyone ever study mathematics?


Posted in Engineering, Labs
By Frank Thomas on November 11, 2013

The eternal questions that follow nearly all students of the discipline of mathematics: “why would you ever study math? What on earth would you ever do with a math degree? When do you start teachers’ college?” Each question is more infuriating than the last. But over the years I grew to understand why people ask …

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