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
APRIL 25, 2023
A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. It is simply unaware of truthfulness, as it is optimized to predict the most likely response based on the context of the current conversation, the prompt provided, and the data set it is trained on.
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Sisense
JULY 24, 2019
When the app is first opened, the user may be searching for a specific song that was heard while passing by the neighborhood cafe, or the user may want to be surprised with, let’s say, a song from the new experimental album by a Yemen Reggae folk artist. when the user actually meant to compare between Q1 2018 to the whole of 2017?
The Unofficial Google Data Science Blog
JULY 22, 2020
Instead, we focus on the case where an experimenter has decided to run a full traffic ramp-up experiment and wants to use the data from all of the epochs in the analysis. When there are changing assignment weights and time-based confounders, this complication must be considered either in the analysis or the experimental design.
Domino Data Lab
JULY 2, 2019
SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. Here’s a sampler of related papers and articles if you’d like to dig in further: “ Synthesizing Programs with Deep Learning ” – Nishant Sinha (2017-03-25). “
Domino Data Lab
MAY 8, 2019
Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Challenges for Transparency ”. Riccardo Guidotti, et al.
O'Reilly on Data
MARCH 23, 2023
Many of these go slightly (but not very far) beyond your initial expectations: you can ask it to generate a list of terms for search engine optimization, you can ask it to generate a reading list on topics that you’re interested in. It was not optimized to provide correct responses. It has helped to write a book.
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