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Fortunately, a recent survey paper from Stanford— A Critical Review of Fair Machine Learning —simplifies these criteria and groups them into the following types of measures: Anti-classification means the omission of protected attributes and their proxies from the model or classifier. What machine learning means for software development”.
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Datacollection is nothing new, but the introduction of mobile devices has made it more interesting and efficient. But now, mobile datacollection means information can be digitally recording on the mobile device at the source of its origin, eliminating the need for data entry after the information is collected.
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12: Almost all reporting is off custom reports. #11: 7: 25% of all analytical effort is dedicated to data visualization/enhancing data's communicative power. #6: 6: All automated reports are turned off on a random day/week/month each quarter to assess use/value. #5: Reporting Squirrels vs. Analysis Ninjas.
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Hour-by-hour report please. :)? , I am having issues prioritizing 1) recommending fixing on site issues affecting real traffic levels versus 2) correcting significant configuration issues in Analytics measuring current site traffic. If there is anything you can measure, even with your broken analytics implementation, do that first.
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You just have to have the right mental model (see Seth Godin above) and you have to… wait for it… wait for it… measure everything you do! For everything you do it is important to measure your effectiveness of all three phases of your effort: Acquisition. You’re trying to measure how well you are doing to: Send emails.
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[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 do use them, please consider the datacollection methodology.
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