Machine Learning Optimization Risk 
O'Reilly on Data
NOVEMBER 13, 2018
As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Let’s begin by looking at the state of adoption.
O'Reilly on Data
MAY 21, 2019
Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. I will highlight the results of a recent survey on machine learning adoption, and along the way describe recent trends in data and machine learning (ML) within companies.
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O'Reilly on Data
JULY 15, 2019
As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk. Model risk management.
Smart Data Collective
FEBRUARY 28, 2023
Machine learning technology has already had a huge impact on our lives in many ways. There are numerous ways that machine learning technology is changing the financial industry. However, machine learning can also help financial professionals as well. What is risk parity? Who invented risk parity?
Smart Data Collective
OCTOBER 13, 2021
It’s similar to prices – price optimization through machine learning is a great tool to grow your revenue. What can you learn from real-market examples? That’s where machine learning algorithms come into place. That’s where machine learning algorithms come into place. How exactly?
CIO Business Intelligence
NOVEMBER 14, 2024
Such a large-scale reliance on third-party AI solutions creates risk for modern enterprises. As a result, many companies are now more exposed to security vulnerabilities, legal risks, and potential downstream costs. They can lean on AMPs to mitigate MLOps risks and guide them to long-term AI success.
O'Reilly on Data
DECEMBER 10, 2019
Roughly a year ago, we wrote “ What machine learning means for software development.” Karpathy suggests something radically different: with machine learning, we can stop thinking of programming as writing a step of instructions in a programming language like C or Java or Python. Instead, we can program by example.
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