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Bringing an AI Product to Market

O'Reilly on Data

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Without clarity in metrics, it’s impossible to do meaningful experimentation. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ).

Marketing 362
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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. A properly set framework will ensure quality, timeliness, scalability, consistency, and industrialization in measuring and driving the return on investment.

Insurance 250
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Designing A/B tests in a collaboration network

The Unofficial Google Data Science Blog

We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. This could create confusion.

Testing 58
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The top 15 big data and data analytics certifications

CIO Business Intelligence

Certifications measure your knowledge and skills against industry- and vendor-specific benchmarks to prove to employers that you have the right skillset. Organization: AWS Price: US$300 How to prepare: Amazon offers free exam guides, sample questions, practice tests, and digital training.

Big Data 126
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Generative AI’s change management challenge

CIO Business Intelligence

And while 68% of leaders believe their companies have implemented adequate measures to ensure responsible use of AI, only 29% of their frontline employees feel that way. With familiarity with generative AI being a key factor for its successful adoption, employees must get a chance to test it themselves.

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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., Taking measurements at parameter settings further from control parameter settings leads to a lower variance estimate of the slope of the line relating the metric to the parameter.

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eCommerce Brands Use Data Analytics for Conversion Rate Optimization

Smart Data Collective

Not only can such patterns create a greater awareness of user interactions, but they can also provide invaluable data on where improvements can be made. Whether you’re optimizing headlines, button colors, product descriptions, or layouts, testing different versions can yield decisive data-driven decisions.