August, 2014

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Building a Bandcamp recommender system (part 1 – motivation)

Data Science and Beyond

I’ve been a Bandcamp user for a few years now. I love the fact that they pay out a significant share of the revenue directly to the artists, unlike other services. In addition, despite the fact that fans may stream all the music for free and even easily rip it, almost $80M were paid out to artists through Bandcamp to date (including almost $3M in the last month) – serving as strong evidence that the traditional music industry’s fight against piracy is a waste of resources and time.

IT 52
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Product Insights for Airbnb

Edwin Chen

I love studying users and products, and think data science can be extremely useful in guiding product/strategy as a whole. So I thought it would be fun to depart from the usual machine learning and engineering things I write about, and do a quick study of Airbnb. Think of this like business analysis, or strategy – from a data science point of view. (It's in slide deck form , of course, because that's how these things roll.).

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VCDX Study Lounge on Sunday at VMworld SF

Nutanix

If you are preparing for your VCDX examination, or even just interested in getting started, Nutanix invites you to come by the VCDX Study Lounge on Sunday at VMworld 2014 in San Francisco.

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Smart Dashboard Modules: Insightful Dimensions And Best Metrics

Occam's Razor

'My last post, perhaps provocatively, called for a reduction of data in executive dashboards (digital, online, offline). More English (IABI, specifically) would lead to a smarter understanding of performance, and of course glory for data practitioners. Here's the post: Strategic & Tactical Dashboards: Best Practices, Examples. In the post Adil commented that he's observed that attribution modeling is missing from most web analytics dashboards.

Metrics 147
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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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How to (almost) win Kaggle competitions

Data Science and Beyond

Last week, I gave a talk at the Data Science Sydney Meetup group about some of the lessons I learned through almost winning five Kaggle competitions. The core of the talk was ten tips, which I think are worth putting in a post (the original slides are here). Some of these tips were covered in my beginner tips post from a few months ago. Similar advice was also recently published on the Kaggle blog – it’s great to see that my tips are in line with the thoughts of other prolific kagglers.

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The baton is passing

Nutanix

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

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Pay-As-You-Grow with Nutanix and VMware Horizon 6

Nutanix

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

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AppSense DesktopNow validated for Nutanix

Nutanix

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

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Announcing Nutanix Cloud Connect

Nutanix

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

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Nutanix establishes next phase Partner Network framework

Nutanix

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Nutanix establishes next phase Partner Network framework

Nutanix

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Nutanix establishes next phase Partner Network framework

Nutanix

20
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Nutanix Arrives as a Mainstream Datacenter Player

Nutanix

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Nutanix Arrives as a Mainstream Datacenter Player

Nutanix

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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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Nutanix Arrives as a Mainstream Datacenter Player

Nutanix

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Blog Post - Variant 2 - Blog Page Template

Nutanix

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Propensity Modeling, Causal Inference, and Discovering Drivers of Growth

Edwin Chen

Imagine you just started a job at a new company. You watched World War Z recently, so you're in a skeptical mood, and given that your last two startups failed from what you believe to be a lack of data, you're giving everything an extra critical eye. You start by thinking about the impact of the sales team. How much extra revenue are they generating for the company?

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Data’s hierarchy of needs

Data Science and Beyond

One of my favourite blog posts in recent times is The Log: What every software engineer should know about real-time data’s unifying abstraction by Jay Kreps. That post comprehensively describes how abstracting all the data produced by LinkedIn’s various components into a single log pipeline greatly simplified their architecture and enabled advanced data-driven applications.

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The Big Payoff of Application Analytics

Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. That’s what drove the five companies in this e-book to change their approach to analytics. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.