DataRobot Blog

JANUARY 10, 2023

ML model builders spend a ton of time running multiple experiments in a data science notebook environment before moving the well-tested and robust models from those experiments to a secure, production-grade environment for general consumption. Capabilities Beyond Classic Jupyter for End-to-end Experimentation. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 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 then proceed with pharmacokinetic modeling, testing the goodness of fit of various models.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

CIO Business Intelligence

MAY 1, 2024

Pilots can offer value beyond just experimentation, of course. McKinsey reports that industrial design teams using LLM-powered summaries of user research and AI-generated images for ideation and experimentation sometimes see a reduction upward of 70% in product development cycle times.

Cost-Benefit 142

Cost-Benefit Metrics Insurance Measurement 142

Insight

MARCH 12, 2020

I tested several different flavors of BERT for use as synopsis classifiers before settling on the DistilBERT model from Hugging Face. Text synopses are ‘tokenized’ with the aid of a reference library. On my test set, this approach resulted in~75–95% accuracy and ~.65 DistilBERT tokenization and embedding, from Jay Alammar.

Modeling 59

Modeling Metadata Publishing Sales 59

O'Reilly on Data

JULY 25, 2023

Swift Papers felt like a well-scoped project to test how well AI handles a realistic yet manageable real-world programming task. I also installed the latest VS Code (Visual Studio Code) with GitHub Copilot and the experimental Copilot Chat plugins, but I ended up not using them much.

Consulting 246

Consulting Interactive Software IT 246

CIO Business Intelligence

APRIL 5, 2023

Midjourney, ChatGPT, Bing AI Chat, and other AI tools that make generative AI accessible have unleashed a flood of ideas, experimentation and creativity. Testing is another area that tends to get neglected, so automated unit test generation will help you get much broader test coverage.

Modeling 102

Modeling Testing Cost-Benefit Experimentation 102

AWS Big Data

JULY 26, 2023

Using augmented ML search and generative AI with vector embeddings Organizations across all verticals are rapidly adopting generative AI for its ability to handle vast datasets, generate automated content, and provide interactive, human-like responses.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

Occam's Razor

AUGUST 12, 2013

Last Interaction/Last Click Attribution model. First Interaction/First Click Attribution Model. Just so we have a visual guide through this learning process, let's use the above image as a reference. Last Interaction/Last Click Attribution model. First Interaction/First Click Attribution Model. I can be nice.

Modeling 161

Modeling Optimization Marketing Interactive 161

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 132

IT Risk Management Interactive Modeling 132

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

Perceptual Edge

AUGUST 26, 2019

Note: In case the term is unfamiliar, “spatial computing” apparently refers to VR, AR, and other related technologies). New conceptions of data are now encoded into the actual application experiences that improve the user’s interaction with their data. (p. Her case is hollow. The evidence suggests otherwise.

Visualization 52

Visualization Cost-Benefit Interactive Experimentation 52

Cloudera

JUNE 6, 2019

When a mix of batch, interactive, and data serving workloads are added to the mix, the problem becomes nearly intractable. We sometimes refer to this as splitting “dev/test” from “production” workloads, but we can generalize the approach by referring to the overall priority of the workload for the business.

Metadata 88

Metadata Data Lake Optimization Strategy 88

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

JULY 2, 2019

Interactive Query Synthesis from Input-Output Examples ” – Chenglong Wang, Alvin Cheung, Rastislav Bodik (2017-05-14). Although not specifically cited by the AutoPandas project (apologies if I missed a reference?) A Program Synthesis Primer ” – Aws Albarghouthi (2017-04-24). Software writes Software?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

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

Domino Data Lab

AUGUST 22, 2019

Note: Lemmatization, a more sophisticated alternative to stemming, requires the use of a reference vocabulary. 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.]. and 11.7).].

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

datapine

JANUARY 31, 2022

Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was. What Are The Benefits of Business Intelligence?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214