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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. Ongoing monitoring of critical metrics is yet another form of experimentation.

Marketing 362
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eCommerce Brands Use Data Analytics for Conversion Rate Optimization

Smart Data Collective

Collecting Relevant Data for Conversion Rate Optimization Here is some vital data that e-commerce businesses need to collect to improve their conversion rates. Identifying Key Metrics for Conversion Rate Optimization Data collection and analysis are both essential processes for optimizing your conversion rate.

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Digital listening reveals 3 leading innovation drivers

CIO Business Intelligence

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data.

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Next Stop – Predicting on Data with Cloudera Machine Learning

Cloudera

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature.

Metrics 156
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The AIgent: Using Google’s BERT Language Model to Connect Writers & Representation

Insight

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Data Collection The AIgent leverages book synopses and book metadata. The latter is any type of external data that has been attached to a book? On my test set, this approach resulted in~75–95% accuracy and ~.65

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Web Analytics: An Hour A Day

Occam's Razor

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). What ideas to test first on your site? Bonus: Interactive CD. It is a book about Web Analytics 2.0.