March, 2017

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Artificial Intelligence: Implications On Marketing, Analytics, And You

Occam's Razor

A rare post today. It looks a little further out into the future than I normally tend to. It attempts to simplify a topic that has more than it’s share of coolness, confusion and complexity. While the phrase Artificial Intelligence has been around since the first human wondered if she could go further if she had access to entities with inorganic intelligence, it truly jumped the shark in 2016.

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Product And Platform

Bruno Aziza

Products do not often exhibit long-term disruptive value. Platforms do. From Snap to Amazon, companies that invested in underlying platform technology were able to exert lasting influence over the way in which people consume content and information.

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Attributing a deep network’s prediction to its input features

The Unofficial Google Data Science Blog

By MUKUND SUNDARARAJAN, ANKUR TALY, QIQI YAN Editor's note: Causal inference is central to answering questions in science, engineering and business and hence the topic has received particular attention on this blog. Typically, causal inference in data science is framed in probabilistic terms, where there is statistical uncertainty in the outcomes as well as model uncertainty about the true causal mechanism connecting inputs and outputs.

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Beware the Data Governance Ides of March

Jim Harris

Morte de Césare (Death of Caesar) by Vincenzo Camuccini , 1798 Today is the Ides of March (March 15), which back in 44 BC was definitely not a good day to be Julius Caesar, who was literally stabbed in the back by the Roman Senate during his assassination in the Theatre of Pompey (as depicted above), which was spearheaded by Brutus and Cassius in a failed attempt to restore the Roman Republic, but instead resulted in a series of civil wars that ultimately led to the establishment of the permanen

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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Office Politics: A survivor’s guide for programmers and data scientists

DSI Analytics

Office Politics: A survivor’s guide for data scientists Everyone gets sunk by office politics at some point in their career, but data scientists are in some ways especially ill-prepared to navigate the unspoken rules and hidden agendas that together form a critical part of the corporate world. There are those who leverage office politics as […].

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Top Data Science Resources on the Internet right now

MLWhiz

I have been looking to create this list for a while now. There are many people on quora who ask me how I started in the data science field. And so I wanted to create this reference. To be frank, when I first started learning it all looked very utopian and out of the world. The Andrew Ng course felt like black magic. And it still doesn’t cease to amaze me.

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The Art Of Building Platforms

Bruno Aziza

You do not build a product in a vacuum. We build platforms with highly cross-functional teams that include people from partnerships, policy, support, engineering, product marketing, analytics, design, research, and many other groups.

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Social Analytics are the LEAST of Analytics Leaders’ Problems

Jenny Sussin

This is my second year attending Gartner’s Data and Analytics Summit and I love it. I love it because the conversations I have with analytics leaders about social analytics shed brilliant light on why social analytics has been, and often continues to be, the responsibility of a separate social marketing team. For marketers, social analytics can be game changing.

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Nutanix Xpress: The Little HCI Engine That Could

Nutanix

This morning on May 24th, 2016, we announced Nutanix Xpress – our first product line dedicated just to small and medium-sized businesses.

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Avoiding Costly Recruiting Mistakes: The Importance Of High Standards

Bruno Aziza

MongoDB CEO Dev Ittycheria explains how expensive poor hiring decisions are and why the devil you know may be better than the devil you don’t.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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The FCC Just Made Your Online World Less Private

Bruno Aziza

A new White House administration and Congress are moving quickly on high-profile policy like immigration and health care – issues that are dominating the headlines. Another potential policy shift that is getting much less mainstream media attention could threaten the privacy of nearly every American.

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7 Key Facts You Need to Know Before Investing In Drone Technology

Bruno Aziza

With a broad range of practical applications and rapidly evolving technology, drones offer huge untapped potential, but not every market offers equal opportunities for growth. Here are seven facts and forecasts to know before investing.

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How Digital Disruption Transcends Industry Borders

Bruno Aziza

7 questions all business and IT leaders should be asking.

IT 59
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Basics Of Linear Regression

MLWhiz

Today we will look into the basics of linear regression. Here we go : Contents Simple Linear Regression (SLR) Multiple Linear Regression (MLR) Assumptions 1. Simple Linear Regression Regression is the process of building a relationship between a dependent variable and set of independent variables. Linear Regression restricts this relationship to be linear in terms of coefficients.

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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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Top advice for a Data Scientist

MLWhiz

A data scientist needs to be Critical and always on a lookout of something that misses others. So here are some advices that one can include in day to day data science work to be better at their work: 1. Beware of the Clean Data Syndrome You need to ask yourself questions even before you start working on the data. Does this data make sense? Falsely assuming that the data is clean could lead you towards wrong Hypotheses.

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Act II: Thinking Global, Acting Local

Nutanix

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