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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

With a framework and Enterprise MLOps, organizations can manage data science at scale and realize the benefits of Model Risk Management that are received by a wide range of industry verticals. It was first defined by the US Federal Reserve and Office of the Comptroller of the Currency ( SR 11-7 ) in April 2011. What Is Model Risk?

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Unintentional data

The Unofficial Google Data Science Blog

We data scientists now have access to tools that allow us to run a large numbers of experiments, and then to slice experimental populations by any combination of dimensions collected. Make experimentation cheap and understand the cost of bad decisions. This leads to the proliferation of post hoc hypotheses.

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Six Nudges: Creating A Sense Of Urgency For Higher Conversion Rates!

Occam's Razor

Present a yummy spreadsheet that quantifies the cost of inaction , how much money you’ll lose by not delivering a 25% improvement every week. Yet, this incredible benefit was not a part of YouTube TV’s merchandizing strategy from day one. Checkout the Kimbao Sauvignon Blanc you can see sales and would buy it again rates since 2011.

Strategy 124
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How To Suck At Social Media: An Indispensable Guide For Businesses

Occam's Razor

The benefits are numerous. In my Oct 2011 post, Best Social Media Metrics , I'd created four metrics to quantify this value. Economic Value (EcV) is the value of short and long-term revenue and cost savings. The serious point is that when we choose to invest in Social Media, it comes at a cost. The opportunity cost.

B2B 167
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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

During their data preprocessing steps, Maas and his coworkers decided to leave in stop words because they are “indicative of sentiment.” [Note: In more technical machine learning terms, the cost function of the skip-gram architecture is to maximize the log probability of any possible context word from a corpus given the current target word.]

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When models are everywhere

O'Reilly on Data

Television only lacked the immediate feedback that comes with clicks, tracking cookies, tracking pixels, online experimentation, machine learning, and “agile” product cycles. Regardless of how we think of ourselves, humans aren’t terribly good at trading off short-term stimulus against long-term benefits. And the cycle goes on.

Modeling 188