Data eBook Machine Learning Metrics 
OverOps
AUGUST 12, 2019
All the data in the world means nothing if it’s not the right data. But when it comes to delivering reliable software and troubleshooting issues, what is the right data? When it comes to CR, it’s not just about what data you can capture, but how you analyze and leverage it. Code Metrics.
TIBCO - Connected Intelligence
MAY 20, 2020
Just as you wouldn’t train athletes and not have them compete, the same can be said about data science & machine learning (ML). Model Ops is the process of operationalizing data science by getting data science models into production and then managing them. Model Operations, or Model Ops, is the answer.
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DataRobot
MAY 10, 2022
Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . No longer is the modeler only limited to using linear models; they may now make use of varied data sources (both structured and unstructured) to build significantly higher performing models to power business processes.
CircleCI
NOVEMBER 18, 2021
IT infrastructure increasingly relies on complicated deployments, multi-cloud architectures, and huge amounts of data. These events occur when a team establishes inadequate settings for cloud data protection. AIOps uses machine learning and big data to assist IT operations. Take cloud misconfiguration, for example.
Tenable
APRIL 8, 2019
Predictive Prioritization remains true to the CVSS framework (see figure below), but enhances it by replacing the CVSS exploitability and exploit code maturity components with a threat score produced by machine learning – powered by a diverse set of data sources. If exploited, will have a major impact. Past threat sources (e.g.,
DataRobot
APRIL 20, 2021
In this installment, I’ll cover four key elements of trusted AI that relate to the performance of a model: data quality, accuracy, robustness and stability, and speed. Trustworthy AI is built on a foundation of high-quality data. When you have the data in hand, assess its quality. Quality Input Means Quality Output.
DataRobot
MAY 26, 2022
Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. Not only does this include reviewing the assumptions in selecting the input features and data, it also requires analyzing the model’s behavior over a variety of input values.
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