The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

APRIL 16, 2019

by MICHAEL FORTE Large-scale live experimentation is a big part of online product development. This means a small and growing product has to use experimentation differently and very carefully. This blog post is about experimentation in this regime. Such decisions involve an actual hypothesis test on specific metrics (e.g.

Experimentation 68

Experimentation Sales Metrics Measurement 68

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

Alation

SEPTEMBER 28, 2022

Automated testing to ensure data quality. Alation provides robust DataOps solutions that help you foster collaboration, build trusted data solutions, automate testing & monitoring, and visualize data pipelines. Daily Interactions. Easy-to-experiment data development environment. Monitoring and reporting of processes.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature. Identify, hypothesize, test, react. But at the same time, they had to have a real test of an actual feature. You don’t need a beautiful beast to go out and test.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Domino Data Lab

DECEMBER 4, 2020

Domino Lab supports both interactive and batch experimentation with all popular IDEs and notebooks (Jupyter, RStudio, SAS, Zeppelin, etc.). Once all packages have been imported, we can move on to loading our test data. We can group by study arm and calculate various statistics as mean and standard deviation.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

The Unofficial Google Data Science Blog

JULY 31, 2016

At the end of the semester, you administer a proficiency test to the students and compare test performance across the groups. For example, you might compare the average test score among students exposed to the new curriculum to the average score among the controls. The second source of dependence comes from student interactions.

Experimentation 42

Experimentation Testing Measurement Metrics 42

Ontotext

APRIL 3, 2024

Nimit Mehta: I think that 2024 is going to be a buckle-down year, but, at the same time, we’ll see a rapid explosion of experimentation. ” So, maybe they are open to some testing and exploration, but when it’s prime time, larger organizations won’t run the risk of putting something untested. These are not statistical inferences.

Technology 59

Technology Risk Digital Transformation Measurement 59

Insight

APRIL 28, 2020

How will they interact with product, engineering, sales, or marketing? you’re looking for a collaborator who can work and communicate well with you and your team, as well as anyone else that interacts with your team. What to evaluate: How will this person contribute to your culture? Will they be a strategic thought partner?

Data-driven 53

Data-driven Data Science Experimentation Measurement 53

Domino Data Lab

AUGUST 26, 2019

This control prevents overfitting and reduction in predictive accuracy on new test data. If we don’t like the result of testing after training, we can also select an entirely different learning machine with different internals. We can take this model to other, novel data and perform a final hold-out test assessment.

Testing 79

Testing Modeling Machine Learning Metrics 79

The Unofficial Google Data Science Blog

MARCH 22, 2018

But what if users don't immediately uptake the new experimental version? Background At Google, experimentation is an invaluable tool for making decisions and inference about new products and features. by DANIEL PERCIVAL Randomized experiments are invaluable in making product decisions, including on mobile apps.

Experimentation 62

Experimentation Measurement Modeling Statistics 62

Domino Data Lab

MAY 8, 2019

They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Agile was originally about iterating fast on a code base and its unit tests, then getting results in front of stakeholders. evaluate the effects of models on human subjects.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Insight

MARCH 12, 2020

The most powerful approach for the first task is to use a ‘language model’ (LM), i.e. a statistical model of natural language. I tested several different flavors of BERT for use as synopsis classifiers before settling on the DistilBERT model from Hugging Face. On my test set, this approach resulted in~75–95% accuracy and ~.65

Modeling 59

Modeling Metadata Publishing Sales 59

Occam's Razor

SEPTEMBER 13, 2016

Hypothesis development and design of experimentation. Ok, maybe statistical modeling smells like an analytical skill. If these 50 pass the sniff test, send the survey. Don't repeat things for years without constantly stress-testing for reality. . + Pattern recognition and understanding trends. Take 10 mins each.

Modeling 127

Modeling Reporting Strategy Consulting 127

Occam's Razor

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. Usually at least a test. Meanwhile see if you can convince your HiPPO to run a small test while you look for a case study (and a job). ]. Likely not.

Analytics 118

Analytics Consulting Metrics Experimentation 118

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

The beliefs of this community are always evolving, and the process of thoughtfully generating, testing, refuting and accepting ideas looks a lot like Science. It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] Note: A test set of 19,500 such analogies was developed by Tomas Mikolov and his colleagues in their 2013 word2vec paper. This test set is available at download.tensorflow.org/data/questions-words.txt.]. Note that the final test word in Table 11.2—ma’am—is

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Occam's Razor

JUNE 6, 2007

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). What ideas to test first on your site? Bonus: Interactive CD. It is a book about Web Analytics 2.0.

Analytics 60

Analytics Metrics Marketing Dashboards 60

CIO Business Intelligence

DECEMBER 6, 2023

Microsoft called the poll an error and promised to investigate, but it already seems to clearly breach several of the company’s own principles of responsible AI usage , such as inform people that they’re interacting with an AI system, and guidelines for human-AI interaction.

IT 128

IT Risk Management Interactive Modeling 128

IBM Big Data Hub

SEPTEMBER 25, 2023

Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes. If the exploratory work needs to move on to testing and production, they can plan appropriately. What is Presto?

OLAP 90

OLAP Data Lake Data-driven Snapshot 90