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What you need to know about product management for AI

O'Reilly on Data

All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies.

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Glossary of Digital Terminology for Career Relevance

Rocket-Powered Data Science

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). They cannot process language inputs generally. See [link]. Edge Computing (and Edge Analytics): Industry 4.0:

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. Our main tools are the difference-of-convex-programs paradigm[9] and the embedded conic solver[10]; the reference [11] is also very useful.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

This post considers a common design for an OCE where a user may be randomly assigned an arm on their first visit during the experiment, with assignment weights referring to the proportion that are randomly assigned to each arm. For example, imagine a fantasy football site is considering displaying advanced player statistics.

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Methods of Study Design – Experiments

Data Science 101

Some pitfalls of this type of experimentation include: Suppose an experiment is performed to observe the relationship between the snack habit of a person while watching TV. Bias can cause a huge error in experimentation results so we need to avoid them. REFERENCES. Statistics Essential for Dummies by D. McCabe & B.

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Einstein Studio 1: What it is and what to expect

CIO Business Intelligence

For teams that want to boil down their own data into predictive tools, Model Builder will turn all those records of past purchases sitting in the data lake into a big statistical hair ball of tendencies that passes for an AI these days. Salesforce is pushing the idea that Einstein 1 is a vehicle for experimentation and iteration.

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What Are ChatGPT and Its Friends?

O'Reilly on Data

There’s a very important difference between these two almost identical sentences: in the first, “it” refers to the cup. In the second, “it” refers to the pitcher. And it can look up an author and make statistical observations about their interests. She poured water from the pitcher to the cup until it was empty.

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