Remove 2006 Remove Metrics Remove Optimization Remove Testing
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Analytics On The Bleeding Edge: Transforming Data's Influence

Occam's Razor

The first component is a gloriously scaled global creative pre-testing program. We pre-test pretty much everything in an online lab ish environment, and predict whether a piece of a TV or Billboard or Radio or YouTube or Facebook creative will be successful. Matched market tests. Creative is the thing you see in the ad.

Analytics 131
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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.

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A guide to efficient Oracle implementation

IBM Big Data Hub

The platform has been used to modernize and unify the information technology (IT) ecosystem of major financial firms, simplify human capital management (HCM) across brands’ subsidiaries, and optimize reporting processes in complex healthcare settings.

Testing 80
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Excellent Analytics Tip #8: Measure the Real Conversion Rate & "Opportunity Pie"

Occam's Razor

And no that is not Visits or Total Visitors in the denominator, for my perspective on why that is sub-optimal click here and read the part about Why use Unique Visitors.]. The problem is that you are there just to look at the car, maybe take it for a test drive. Is Real Conversion Rate metric a good one? What do you think?

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Best Web Metrics / KPIs for a Small, Medium or Large Sized Business

Occam's Razor

I am going to attempt to significantly simply your life by recommending the critical few metrics you should use to analyze performance of your digital marketing campaigns and website. Recommend metrics / KPIs you can use based on the size of your company. Best Metrics / KPIs for Small Business Websites. Obsess about this metric.

Metrics 151
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Position2’s Arena Calibrate helps customers drive marketing efficiency with Amazon QuickSight Embedded

AWS Big Data

Position 2 was established in 2006 in Silicon Valley and has a clientele spanning American Express, Lenovo, Fujitsu, and Thales. After all that, we were still missing out on proactive analysis that identifies trends and uncovers optimization opportunities. We work with clients ranging from VC-funded startups to Fortune 500 firms.

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Building a Named Entity Recognition model using a BiLSTM-CRF network

Domino Data Lab

from keras import optimizers from keras.models import Model from keras.models import Input from keras_contrib.layers import CRF from keras_contrib import losses from keras_contrib import metrics. Number of sentences in the training dataset: 43163 Number of sentences in the test dataset : 4796. Evaluation and testing.

Modeling 111