2016 Experimentation Machine Learning 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.
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. An ML-related topic, “models,” was No.
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Domino Data Lab
AUGUST 22, 2019
Note: In more technical machine learning terms, the cost function of the skip-gram architecture is to maximize the log probability of any possible context word from a corpus given the current target word.] You can home in on an optimal value by specifying, say, 32 dimensions and varying this value by powers of 2. Joulin, A.,
DataRobot Blog
SEPTEMBER 22, 2022
Since 2016, DataRobot has aligned with customers in finance, retail, healthcare, insurance and more industries in France with great success, with the first customers being leaders in the insurance space. . Organizations are no longer satisfied with “experimental” AI, they want AI implemented in business processes that drive results at scale.
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.
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