Jet Global

JUNE 25, 2020

Based on 20 years of research findings and heavily informed by insights gleaned from the 2008 financial downturn, the list deserves review: Taking Bigger Bets. Combining Budget Models. Fighting Scope Creep. Funding Critical Initiatives. Facilitating Risk Taking. Learning the Customer. Cutting the Losses. Trimming Costs Carefully.

Uncertainty 52

Uncertainty Reporting Risk Metrics 52

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

Domino Data Lab

MAY 20, 2021

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. def get_neigbours(M, k): nn = NearestNeighbors(n_neighbors=k+1, metric="euclidean").fit(M) from sklearn.neighbors import NearestNeighbors from random import randrange. return synthetic.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

O'Reilly on Data

MAY 27, 2020

These report cards have changed the way that cardiac surgeons in New York do their jobs, but thirty years on, it’s still not clear whether the metrics make things better. Google’s Model Cards , for instance, include discussion in plain language about the tradeoffs engineers had to make when designing a system.

Risk 355

Risk Testing Reporting Measurement 355

Occam's Razor

OCTOBER 14, 2014

See step four in the process for creating your Digital Marketing and Measurement Model.]. If you've read my first book Web Analytics: An Hour A Day, you know that I've advocated this strategy since 2008! Conversion rate is one of those metrics that I strongly encourage you only create benchmarks for from your own data.

Key Performance Indicator 133

Key Performance Indicator Metrics Reporting Marketing 133

CIO Business Intelligence

JUNE 27, 2022

Sentry was started as an open source project by David Cramer in 2008 to provide monitoring services for application developers. Tyson: You’re coming up to two years since you added Sentry’s ability to monitor for performance which has some pretty fine-grained metrics in terms of identifying where bottlenecks are located in code.

Software 97

Software Experimentation Testing Marketing 97

Edwin Chen

OCTOBER 23, 2011

So instead of having our models predict the 4-star rating itself, we could first try to remove the effect of the baseline predictors (the first three components) and have them predict the specific 0.7 Neighborhood Models. Let’s now look at some slightly more sophisticated models. the baseline rating) - 0.5 (the

Metrics 101

Metrics Modeling Interactive IT 101

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. Since 2008, teams working for our founding team and our customers have delivered 100s of millions of data sets, dashboards, and models with almost no errors. Tie tests to alerts.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Occam's Razor

NOVEMBER 18, 2014

Short story #2: Predictive Modeling, Quantifying Cost of Inaction. You can hover over each box to get a sense of the key metrics. Short story #2: Predictive Modeling, Quantifying Cost of Inaction. The work of the New York Times team inspired me it to do some predictive modeling for inaction in our world of digital marketing.

Visualization 143

Visualization Slice and Dice Predictive Modeling Metrics 143

O'Reilly on Data

JANUARY 25, 2021

in 2008 and continuing with Java 8 in 2014, programming languages have added higher-order functions (lambdas) and other “functional” features. Models are neither code nor data, and we don’t have adequate tools for versioning models either (though tools like MLflow are a start). Starting with Python 3.0

Machine Learning 362

Machine Learning Software Testing Technology 362

Jet Global

NOVEMBER 23, 2020

In this model, your monthly income is split into the following categories: 50 percent for needs, 30 percent for wants, 20 percent for debts and savings. Since its launch during the 2008 financial crisis, Planet Money, a podcast from National Public Radio, has won many awards. Can you see it in your numbers?

KPI 52

KPI Finance Dashboards Data Processing 52

Domino Data Lab

JULY 22, 2019

how “the business executives who are seeing the value of data science and being model-informed, they are the ones who are doubling down on their bets now, and they’re investing a lot more money.” and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109