2017 Interactive Metrics Risk 
O'Reilly on Data
APRIL 23, 2024
They published the original Transformer paper (not quite coincidentally called “Attention is All You Need”) in 2017, and released BERT , an open source implementation, in late 2018, but they never went so far as to build and release anything like OpenAI’s GPT line of services. I think not.
CIO Business Intelligence
MAY 16, 2023
higher [in 2022] than in 2017.” Blockchain Challenges Privacy and Security: The nature of blockchains as a public ledger presents personal privacy and security risks that likely limit the technology’s adoption in sensitive industries such as healthcare.
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Cloudera
APRIL 7, 2021
A 2017 PWC survey of over 100 global insurance company CEOs revealed that the number one objective of these CEOs was to “get closer to their customers and to better understand their evolving needs.” Changing Business Models. Data — Too much and Too little. The Hunt for Talent. Yet they need to address the above issues to make this a reality.
BizAcuity
APRIL 28, 2019
is delinquent as of June 30th, 2017. An improvement of 50% in debt collection was seen in just 3 months time, that too without any loss on customer interaction. Their issue at hand was to decrease the Portfolio at Risk. According to a Federal Bank report, more than $600 billion of household debt in the U.S.
Data Insight
APRIL 15, 2019
We reward and punish based on our last interaction with an organisation and are not afraid to take to social channels to articulate our experiences – whether it be good or bad – to also influence our peer’s choices. That’s a massive shift in quite a short time frame from traditional metrics without us even realising it.
Cloudera
MAY 18, 2021
These interactions are captured and the resulting synthetic data sets can be analysed for a number of applications, such as training models to detect emergent fraudulent behavior, or exploring “what-if” scenarios for risk management. Value-at-Risk (VaR) is a widely used metric in risk management. Intraday VaR.
The Unofficial Google Data Science Blog
APRIL 23, 2024
the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.
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