Experimentation Marketing Statistics Uncertainty 
O'Reilly on Data
MARCH 31, 2020
You’re responsible for the design, the product-market fit, and ultimately for getting the product out the door. 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. Machine learning adds uncertainty.
The Unofficial Google Data Science Blog
DECEMBER 14, 2021
by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.
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CIO Business Intelligence
JANUARY 2, 2024
CIOs are readying for another demanding year, anticipating that artificial intelligence, economic uncertainty, business demands, and expectations for ever-increasing levels of speed will all be in play for 2024. He plans to scale his company’s experimental generative AI initiatives “and evolve into an AI-native enterprise” in 2024.
CIO Business Intelligence
JUNE 28, 2023
These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As To address the challenges, the company has leveraged a combination of computer vision, neural networks, NLP, and fuzzy logic.
IBM Big Data Hub
APRIL 18, 2024
LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. Here are some areas where organizations are seeing a ROI: Text (83%) : Gen AI assists with automating tasks like report writing, document summarization and marketing copy generation.
Occam's Razor
APRIL 8, 2013
Experiments come in all shapes and sizes: A marketing campaign. Try to understand your market. Read up on ways that companies are growing their business, from growth hacking to content marketing, and use that as inspiration. They might deal with uncertainty, but they're not random. Do it now; we'll wait.
O'Reilly on Data
DECEMBER 9, 2019
Because of this trifecta of errors, we need dynamic models that quantify the uncertainty inherent in our financial estimates and predictions. Practitioners in all social sciences, especially financial economics, use confidence intervals to quantify the uncertainty in their estimates and predictions.
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