Jen Stirrup

FEBRUARY 1, 2023

The effects of AI will be magnified in the coming decade as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning.

Recreation/Entertainment 63

Recreation/Entertainment Testing Advertising Insurance 63

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

Paul Blogs on BI

MARCH 25, 2020

This first metric requires people to be tested and, as we all know, that is only possible in places where testing is available (and confirmation takes a few days) and only a fraction of people have been tested. As more testing becomes available this first metric will increase significantly.

Business Intelligence 51

Business Intelligence Measurement Metrics Cost-Benefit 51

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. We rely heavily on automated testing. Tyson: That belief in your vision when it’s tested—that is tough! million developers today. I thought, really?! How do you get to that level of automation?

Software 113

Software Experimentation Testing Marketing 113

Sisense

APRIL 2, 2019

The DevOps movement started to come together sometime between 2007 and 2008. This is when IT operations and software development communities started to talk about problems in the software industry, specifically around the traditional software development model. It’s also shaping the way BI and Analytics are deployed.

Software 80

Software Testing Enterprise IT 80

AWS Big Data

FEBRUARY 16, 2023

As a QuickSight administrator, you can use AWS CloudFormation templates to migrate assets between distinct environments from development, to test, to production. AWS CloudFormation helps you model and set up your AWS resources so you can spend less time managing those resources and more time focusing on your applications that run in AWS.

Data Warehouse 81

Data Warehouse Sales Visualization Data Processing 81

AWS Big Data

APRIL 25, 2023

However, for quick testing purposes, we demonstrate how to manually run the flow on demand. Summary In this post, we showed how you can support a cross-account model to exchange data between different partners with different SaaS integrations using Amazon AppFlow. Go to the AppFlow ( producer-flow ) in the producer account.

Sales 73

Sales Visualization Software Marketing 73

O'Reilly on Data

SEPTEMBER 19, 2023

” Consider the structural evolutions of that theme: Stage 1: Hadoop and Big Data By 2008, many companies found themselves at the intersection of “a steep increase in online activity” and “a sharp decline in costs for storage and computing.” And it (wisely) stuck to implementations of industry-standard algorithms.

Machine Learning 254

Machine Learning Testing Modeling Cost-Benefit 254

O'Reilly on Data

JULY 15, 2019

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Sources of model risk. Model risk management. Image by Ben Lorica.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

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

AWS Big Data

FEBRUARY 1, 2024

Large language models (LLMs) are becoming increasing popular, with new use cases constantly being explored. This is where model fine-tuning can help. Before you can fine-tune a model, you need to find a task-specific dataset. Next, we use Amazon SageMaker JumpStart to fine-tune the Llama 2 model with the preprocessed dataset.

Metadata 98

Metadata Modeling Data Processing Unstructured Data 98

O'Reilly on Data

MAY 27, 2020

Under school district policy, each of Audrey’s eleven- and twelve-year old students is tested at least three times a year to determine his or her Lexile, a number between 200 and 1,700 that reflects how well the student can read. They test each student’s grasp of a particular sentence or paragraph—but not of a whole story.

Risk 355

Risk Testing Measurement Reporting 355

CIO Business Intelligence

APRIL 4, 2024

The good news is that you can ask any of the large language models (LLMs) like ChatGPT to rewrite paragraphs or sections for improved comprehension or make it more concise. Delete old data I lived in Hong Kong 2008-2013 and one of my most pleasurable weekends was a trip to see an incredible band at the MGM hotel in Macau.

Cost-Benefit 96

Cost-Benefit Data Governance Testing Modeling 96

O'Reilly on Data

JULY 25, 2023

I’m a professor who is interested in how we can use LLMs (Large Language Models) to teach programming. And if I switch tabs to view a paper from 2008, then a song from 2008 could start up. Swift Papers felt like a well-scoped project to test how well AI handles a realistic yet manageable real-world programming task.

Consulting 246

Consulting Interactive Software IT 246

CIO Business Intelligence

MAY 22, 2024

Vietnam already plays host to Intel’s largest plant for silicon test and assembly, while other giants are looking to join or expand. There are many countries around the world who would love to have [Vietnam’s] ability to do assembly, testing and packaging,” Fernandez said. “[It It has] the potential to become a powerhouse.”

Manufacturing 106

Manufacturing Data Processing Testing Software 106

CIO Business Intelligence

MARCH 22, 2022

A certified lead auditor, hacking forensic investigator, and security analyst, Tiwari is an IT veteran from the Indian Navy where he set up the information security and incident response organization, including the formulation of policy frameworks, security audits, product testing, cyber forensics, and risk management. .

Internet Publishing and Broadcasting 98

Internet Publishing and Broadcasting Digital Transformation Insurance Recreation/Entertainment 98

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Cloudera

MARCH 18, 2021

FRTB is designed to address some fundamental weaknesses that did not get addressed in the post-2008 financial crisis regulatory reforms. A revised internal models approach (IMA) combined with an overhaul of the standardized approach (SA). Complete audit trail(s) for data, models, and risk calculations. .

Risk 55

Risk Machine Learning Risk Management Measurement 55

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. Their tests are performed using C4.5-generated note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). Chawla et al.,

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Jen Stirrup

OCTOBER 30, 2022

These propensity models are useful for understanding which customers are most likely to purchase a given set of products. This model can assist in decision making and in focusing marketing efforts. Microsoft offers Data Mining at no extra cost as part of SQL Server 2005 and 2008, which is geared towards the average Excel user.

Data mining 52

Data mining Predictive Analytics Cost-Benefit OLAP 52

BizAcuity

MAY 10, 2022

Amazon strategically went with the pricing model of ‘on-demand’, allowing developers to pay only as-per their computational needs. 2008: Microsoft announces Windows Azure (PaaS) with Azure Blob storage (S3 competitor). AWS rolls out SageMaker, designed to build, train, test and deploy machine learning (ML) models.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

Domino Data Lab

AUGUST 8, 2019

Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. then building machine learning models to recommend methods and potential collaborators to scientists. 2008 – Financial crisis : scientists flee Wall St.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Jet Global

APRIL 22, 2020

As compared to the past crisis of 9/11 and the financial crisis of 2008, the global humanitarian and economic upheaval of COVID-19 is unprecedented. Scenario planning is only as effective as the actions you take, so companies need to create action plans against all the various modeled scenarios.

Uncertainty 59

Uncertainty Testing Management Modeling 59

Occam's Razor

JANUARY 28, 2013

It shows the normal distribution of XS, S, L etc, but it also shows, how cool is this, the Model's size (S in this case), her height, bust, waist and hip size! You can't try the dress on, but this data helps you understand if it will look on you just like it does on the model. The model you see above just starts moving!

Marketing 164

Marketing Insurance Visualization IT 164

Occam's Razor

NOVEMBER 18, 2014

Short story #2: Predictive Modeling, Quantifying Cost of Inaction. 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. Thank goodness for predictive models.

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. In the past decade, a lot of ideas and technologies have come out of the DevOps movement: the source repository as the single source of truth, rapid automated deployment, constant testing, and more.

Machine Learning 363

Machine Learning Software Testing Technology 363

The Unofficial Google Data Science Blog

SEPTEMBER 30, 2016

Setting the Date variable as a label (using the Labels button in the right hand pane) allows us to click on the individual dots and find that both extreme points took place in October of 2008, during the financial crisis when the markets were extra volatile and prone to wild swings. We hope to add more capabilities to the app in the future.

Statistics 53

Statistics Big Data Data Science Marketing 53

Domino Data Lab

MARCH 27, 2019

Select all rows from the 2008 election. votes_2008 <- filter(presidentialElections, year == 2008). The preceding filter() statement is equivalent to extracting the rows using the following base R syntax: # Select all rows from the 2008 election. votes_2008 <- presidentialElections[presidentialElections$year == 2008, ].

Statistics 85

Statistics Data Science Visualization IT 85