October, 2015

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The wonderful world of recommender systems

Data Science and Beyond

I recently gave a talk about recommender systems at the Data Science Sydney meetup (the slides are available here). This post roughly follows the outline of the talk, expanding on some of the key points in non-slide form (i.e., complete sentences and paragraphs!). The first few sections give a broad overview of the field and the common recommendation paradigms, while the final part is dedicated to debunking five common myths about recommender systems.

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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling. A/B testing is used widely in information technology companies to guide product development and improvements.

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MSPs must be Specific Service Providers

Jim Harris

According to my high school English teacher, specificity is the key to effective communication and understanding. Unfortunately for managed service providers ( MSPs ) the term “managed services” does not communicate the specific services they offer, which makes it difficult for potential customers to understand the potential benefits of doing business with MSPs in general, let alone provide the information needed to differentiate one MSP from another in an increasingly crowded marketplace.

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Shell Basics every Data Scientist Should know - Part II(AWK)

MLWhiz

Yesterday I got introduced to awk programming on the shell and is it cool. It lets you do stuff on the command line which you never imagined. As a matter of fact, it’s a whole data analytics software in itself when you think about it. You can do selections, groupby, mean, median, sum, duplication, append. You just ask. There is no limit actually.

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How To Get Promoted In Product Management

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

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Now Generally Available: Nutanix Acropolis 4.5

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Miscommunicating science: Simplistic models, nutritionism, and the art of storytelling

Data Science and Beyond

I recently finished reading the book In Defense of Food: An Eater’s Manifesto by Michael Pollan. The book criticises nutritionism – the idea that one should eat according to the sum of measured nutrients while ignoring the food that contains these nutrients. The key argument of the book is that since the knowledge derived using food science is still very limited, completely relying on the partial findings and tools provided by this science is likely to lead to health issues.

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Shell Basics every Data Scientist Should know -Part I

MLWhiz

Shell Commands are powerful. And life would be like hell without shell is how I like to say it(And that is probably the reason that I dislike windows). Consider a case when you have a 6 GB pipe-delimited file sitting on your laptop and you want to find out the count of distinct values in one particular column. You can probably do this in more than one way.

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Now Generally Available: Nutanix Acropolis 4.5

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Nutanix Technology Champion 2016 Applications Are Open

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Nutanix Technology Champion 2016 Applications Are Open

Nutanix

There’s no question that enterprise application usability has for the most part been left behind.

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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Data scientist as scientist

The Unofficial Google Data Science Blog

by NIALL CARDIN, OMKAR MURALIDHARAN, and AMIR NAJMI When working with complex systems or phenomena, the data scientist must often operate with incomplete and provisional understanding, even as she works to advance the state of knowledge. This is very much what scientists do. Our post describes how we arrived at recent changes to design principles for the Google search page, and thus highlights aspects of a data scientist’s role which involve practicing the scientific method.