2016 Data-driven Experimentation Optimization 
The Unofficial Google Data Science Blog
APRIL 23, 2024
If the relationship of $X$ to $Y$ can be approximated as quadratic (or any polynomial), the objective and constraints as linear in $Y$, then there is a way to express the optimization as a quadratically constrained quadratic program (QCQP). However, joint optimization is possible by increasing both $x_1$ and $x_2$ at the same time.
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 The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace.
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O'Reilly on Data
SEPTEMBER 11, 2019
Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. The term “AI,” meanwhile, is No.
Cloudera
APRIL 9, 2019
In 2016, 60.9% of application workloads were still on-premises in enterprise data centers; by the end of 2017, less than half (47.2%) were on-premises. A hybrid, multi-cloud strategy is the best approach to managing these distributed, heterogeneous data ecosystems. Enterprises are moving to the cloud. Future proof.
O'Reilly on Data
MAY 11, 2020
The Entertainment” is not the result of algorithms, business incentives and product managers optimizing for engagement metrics. Television only lacked the immediate feedback that comes with clicks, tracking cookies, tracking pixels, online experimentation, machine learning, and “agile” product cycles. If that’s not engagement, what is?
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