Data Integration, Metrics, Risk Management and Workshop

Why you should care about debugging machine learning models

O'Reilly on Data

DECEMBER 12, 2019

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. There are at least four major ways for data scientists to find bugs in ML models: sensitivity analysis, residual analysis, benchmark models, and ML security audits. Sensitivity analysis.

Machine Learning

Machine Learning Modeling Testing Risk Management

Your Effective Roadmap To Implement A Successful Business Intelligence Strategy

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Because it is that important. Identify key performance indicators (KPIs).

Business Intelligence

Business Intelligence Strategy Cost-Benefit Key Performance Indicator

Data Leaders Brief

Why you should care about debugging machine learning models

Your Effective Roadmap To Implement A Successful Business Intelligence Strategy

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