Occam's Razor
MARCH 30, 2017
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.
Bruno Aziza
MARCH 22, 2017
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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The Unofficial Google Data Science Blog
MARCH 13, 2017
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.
Jim Harris
MARCH 15, 2017
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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DSI Analytics
MARCH 6, 2017
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 […].
MLWhiz
MARCH 25, 2017
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.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Bruno Aziza
MARCH 17, 2017
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.
Jenny Sussin
MARCH 8, 2017
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.
Nutanix
MARCH 22, 2017
This morning on May 24th, 2016, we announced Nutanix Xpress – our first product line dedicated just to small and medium-sized businesses.
Bruno Aziza
MARCH 20, 2017
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.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
Bruno Aziza
MARCH 16, 2017
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.
Bruno Aziza
MARCH 24, 2017
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.
Bruno Aziza
MARCH 23, 2017
7 questions all business and IT leaders should be asking.
MLWhiz
MARCH 22, 2017
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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MLWhiz
MARCH 4, 2017
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.
Nutanix
MARCH 15, 2017
There’s no question that enterprise application usability has for the most part been left behind.
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