O'Reilly on Data

MARCH 31, 2020

This has serious implications for software testing, versioning, deployment, and other core development processes. There may even be someone on your team who built a personalized video recommender before and can help scope and estimate the project requirements using that past experience as a point of reference.

Management 332

Management Machine Learning Experimentation Metrics 332

Sisense

JANUARY 21, 2020

A new drug promising to reduce the risk of heart attack was tested with two groups. Continuing the previous example, let’s assume that blood pressure is known to be a cause for heart attack and the goal of the test drug is to reduce blood pressure. It really depends on the circumstances. Combined 13/60 = 21.67% 11/60 = 18.3%.

Testing 104

Testing Risk Data-driven Statistics 104

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

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. First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do. Testing out a new feature. Form a hypothesis.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

IBM Big Data Hub

APRIL 18, 2024

AGI, sometimes referred to as strong AI , is the science-fiction version of artificial intelligence (AI), where artificial machine intelligence achieves human-level learning, perception and cognitive flexibility. The doctor uploads the patient’s medical history and recent test results to an AGI-powered medical analysis system.

Cost-Benefit 96

Cost-Benefit Modeling Manufacturing Interactive 96

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. TIME – time points of measured pain score and plasma concentration (in hrs). and 3 to 8 hours.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Ontotext

MARCH 29, 2021

Sadly, the reification had a bad connotation of being overly slow due to the increased number of additional statements needed to identify the reference triple and too verbose to use in SPARQL : 1. : we did practical modeling of various approaches and measured their performance. This was already possible in the very first RDF 1.0

Metadata 59

Metadata IT Modeling Experimentation 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. What are you measuring?

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

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

The Unofficial Google Data Science Blog

JULY 22, 2020

This post considers a common design for an OCE where a user may be randomly assigned an arm on their first visit during the experiment, with assignment weights referring to the proportion that are randomly assigned to each arm. There are two common reasons assignment weights may change during an OCE.

Experimentation 95

Experimentation Statistics Testing Strategy 95

O'Reilly on Data

OCTOBER 19, 2021

ML apps need to be developed through cycles of experimentation: due to the constant exposure to data, we don’t learn the behavior of ML apps through logical reasoning but through empirical observation. but to reference concrete tooling used today in order to ground what could otherwise be a somewhat abstract exercise.

IT 346

IT Testing Experimentation Software 346

Occam's Razor

OCTOBER 21, 2013

This led to the problem we, Marketers, SEOs, Analysts, fondly refer to as not provided. That of course will mean more referring keyword data will disappear. We are headed towards having zero referring keywords from Google and, perhaps, other search engines. Implications of Secure Search Decision. I would humbly suggest not.

Optimization 154

Optimization Reporting Experimentation Metrics 154

Occam's Razor

FEBRUARY 26, 2008

" Or " I proposed testing / surveys / competitive intelligence / Analysts but I was shot down." 1: Implement a Experimentation & Testing Program. # 1: Implement a Experimentation & Testing Program. Here is data from our latest test." And now you have no excuse to avoid testing.

Management 68

Management Experimentation Testing Strategy 68

DataKitchen

MARCH 8, 2023

Manufacturing production errors refer to mistakes or defects that occur during the manufacturing process. DataOps Observability refers to real-time monitoring, detecting, and diagnosing of data status, data pipelines, data tools, and other systems. Measuring these goals is very important to success.

Analytics 130

Analytics Manufacturing Data-driven Data Analytics 130

CIO Business Intelligence

APRIL 18, 2022

The challenge with this approach is that companies end up in what we refer to as the ‘digital trap. Dashboards should be used to monitor the value of an initiative and how value is created, measured by organizational and individual capabilities that support digital transformation, and tracked over time, according to the research brief.

Digital Transformation 145

Digital Transformation Dashboards Cost-Benefit Consulting 145

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. A naïve way to solve this problem would be to compare the proportion of buyers between the exposed and unexposed groups, using a simple test for equality of means.

Statistics 44

Statistics Optimization Modeling Experimentation 44

O'Reilly on Data

MARCH 23, 2023

There’s a very important difference between these two almost identical sentences: in the first, “it” refers to the cup. In the second, “it” refers to the pitcher. Tokens ChatGPT’s sense of “context”—the amount of text that it considers when it’s in conversation—is measured in “tokens,” which are also used for billing.

IT 262

IT Modeling Testing Risk 262

The Unofficial Google Data Science Blog

JULY 31, 2016

The analysis can be straightforward, especially when it's safe to assume that individual observations of an outcome measure are independent. At the end of the semester, you administer a proficiency test to the students and compare test performance across the groups. When analyzing the outcome measure (e.g.,

Experimentation 42

Experimentation Testing Measurement Metrics 42

The Unofficial Google Data Science Blog

MAY 31, 2016

Similarly, we could test the effectiveness of a search ad compared to showing only organic search results. It is important that we can measure the effect of these offline conversions as well. Panel studies make it possible to measure user behavior along with the exposure to ads and other online elements. days or weeks).

Advertising 42

Advertising Testing Sales Statistics 42

AWS Big Data

JULY 26, 2023

The vector engine’s compute capacity used for data ingestion, and search and query are measured in OpenSearch Compute Units (OCUs). From preview to GA and beyond Today, we are excited to announce the preview of the vector engine, making it available for you to begin testing it out immediately.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

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. For example, we might want to stop the process if we measure harmful effects early. What if their uptake rate is not uniform?

Experimentation 62

Experimentation Measurement Modeling Statistics 62

Occam's Razor

AUGUST 12, 2013

I strongly encourage you to read the post and deeply understand all three and what your marketing and measurement possibilities and limitations are. You can even use that column to adjust some of the budget allocation right now, without any attribution modeling, and measure the outcome. All three challenges are important.

Modeling 161

Modeling Optimization Marketing Interactive 161

Occam's Razor

JULY 18, 2011

You just have to have the right mental model (see Seth Godin above) and you have to… wait for it… wait for it… measure everything you do! For everything you do it is important to measure your effectiveness of all three phases of your effort: Acquisition. You’re trying to measure how well you are doing to: Send emails.

Metrics 137

Metrics Marketing Measurement Cost-Benefit 137

Cloudera

JUNE 6, 2019

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. A third strategy splits clusters based on the overall priority of the workloads running on those clusters. Cloudera Manager 6.2

Metadata 87

Metadata Data Lake Optimization Strategy 87

Occam's Razor

AUGUST 10, 2006

We collect all the clickstream data and the objective is to analyze it from a higher plane of reference. No more measuring HITS. This element of the Trinity exists to measure how well is the website doing in meeting the goal of its existence. But for support websites this is measuring Problem Resolution and Timeliness.

Measurement 99

Measurement Experimentation Metrics Testing 99

Occam's Razor

FEBRUARY 7, 2011

Brian Krick: Best way to measure and communicate "available demand" from available channels (social, search, display) for forecast modeling. Additionally, it is exceptionally difficult to measure available demand because 1. please refer to the controlled experimentation section, page 205, in the book for more. ."

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

Occam's Razor

OCTOBER 19, 2010

so you have some reference as to where each item fits (and this will also make it easier for you to pick tools for the priority order referenced in Context #3 above). If you have evolved to a stage that you need behavior targeting then get Omniture Test and Target or Sitespect. You'll measure Task Completion Rate in 4Q (below).

Analytics 135

Analytics Testing Measurement Optimization 135

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

O'Reilly on Data

DECEMBER 9, 2019

We use the diagnostic test results of our regression model to support the reasons why CIs should not be used in financial data analyses. The probability of an event should be measured empirically by repeating similar experiments ad nauseam —either in reality or hypothetically. References. Image Source: Wikimedia Commons.

Statistics 27

Statistics Uncertainty Risk Marketing 27

datapine

JANUARY 31, 2022

For example, in regards to marketing, traditional advertising methods of spending large amounts of money on TV, radio, and print ads without measuring ROI aren’t working like they used to. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. The results?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

Yet when we use these tools to explore data and look for anomalies or interesting features, we are implicitly formulating and testing hypotheses after we have observed the outcomes. We must correct for multiple hypothesis tests. Make experimentation cheap and understand the cost of bad decisions. We ought not dredge our data.

Experimentation 61

Experimentation Testing Statistics Metrics 61