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Rising Tide Rents and Robber Baron Rents

O'Reilly on Data

But in 2013 and 2014, it remained stuck at 83% , and while in the ten years since, it has reached 95% , it had become clear that the easy money that came from acquiring more users was ending. The market was maturing. From 2000 to 2011, the percentage of US adults using the internet had grown from about 60% to nearly 80%.

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Six keys to achieving advanced container monitoring

IBM Big Data Hub

Containers have increased in popularity and adoption ever since the release of Docker in 2013, an open-source platform for building, deploying and managing containerized applications. Organizations might have different needs and different goals regarding their container strategy and must align what they measure with those goals.

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Why you should care about debugging machine learning models

O'Reilly on Data

Residuals are a numeric measurement of model errors, essentially the difference between the model’s prediction and the known true outcome. 8] , [12] Again, traditional model assessment measures don’t tell us much about whether a model is secure. Currency amounts reported in Taiwan dollars. Residual analysis.

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What is ITIL? Your guide to the IT Infrastructure Library

CIO Business Intelligence

ITIL 4 contains seven guiding principles that were adopted from the most recent ITIL Practitioner Exam, which covers organizational change management, communication, and measurement and metrics. Since 2013, ITIL has been owned by Axelos — a joint venture between the Cabinet Office and Capita. How does ITIL reduce costs?

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Benchmarking Performance: Your Options, Dos, Don'ts and To-Die-Fors!

Occam's Razor

[See step four in the process for creating your Digital Marketing and Measurement Model.]. should be 1,356,000), you've set a clear line in the sand as to what performance will be declared a success or a failure at the end of the measurement time period. If you have set the targets for your KPIs up front (Unique Visitors for Sept.

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Perform time series forecasting using Amazon Redshift ML and Amazon Forecast

AWS Big Data

The data contains measurements of electric power consumption in different households for the year 2014. The OBJECTIVE parameter specifies a metric to minimize or maximize the objective of a job. Prepare the data Refer to the following notebook for the steps needed to create this use case. We aggregated the usage data hourly.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.