Smart Data Collective

JULY 9, 2023

This article is going to provide some great insights on developing strategies for unlocking additional value from an online business, which can do a lot to boost revenue and catapult the enterprise to new heights. Experimentation is the key to finding the highest-yielding version of your website elements.

Optimization 74

Optimization Data Analytics Analytics Data-driven 74

CIO Business Intelligence

DECEMBER 19, 2023

In researching this article, I found gaps where CIOs promised capabilities to stakeholders, but implementations and business impacts have lagged expectations. If CIOs don’t improve conversions from pilot to production, they may find their investors losing patience in the process and culture of experimentation.

Digital Transformation 140

Digital Transformation Unstructured Data Machine Learning Risk Management 140

CIO Business Intelligence

JUNE 11, 2024

A 1958 Harvard Business Review article coined the term information technology, focusing their definition on rapidly processing large amounts of information, using statistical and mathematical methods in decision-making, and simulating higher order thinking through applications.

IT 73

IT Digital Transformation Broadcasting Business Objectives 73

Octopai

MAY 2, 2022

Common elements of DataOps strategies include: Collaboration between data managers, developers and consumers A development environment conducive to experimentation Rapid deployment and iteration Automated testing Very low error rates. But the approaches and principles that form the basis of DataOps have been around for decades.

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

Depict Data Studio

JULY 13, 2021

Today’s article comes from Maryfrances Porter, Ph.D. & In the science world, if you have a small group of people and do not find statistical significance, one thing you can do is test a much bigger group! We have used this example before: Scientists discover and test medicines to make sure they work.

Statistics 98

Statistics Testing Recreation/Entertainment Experimentation 98

Decision Management Solutions

DECEMBER 17, 2021

In the recent McKinsey article discussing designing next-generation credit-decisioning models they outlined four best practices for automated credit-decisioning models for banks as they continue their digital transformations. Digital lending based on high-performance credit-decisioning models, says McKinsey, lead to: Increased revenue.

Modeling 52

Modeling Experimentation Visualization Risk 52

Dataiku

APRIL 22, 2022

For companies with small datasets and a mandate to move beyond experimentation, Frugal AI promises to be a way to overcome this challenge. In this article, we took a back-to-basics look at one aspect of Frugal AI. Today, in 2022, the code (i.e.,

Experimentation 59

Experimentation Modeling Business Objectives Manufacturing 59

Cloudera

FEBRUARY 16, 2022

In this article, we explore model governance, a function of ML Operations (MLOps). They define each stage from data ingest, feature engineering, model building, testing, deployment and validation. If a model’s lineage is completely captured, we know exactly what data was used to train, test and validate a model.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Domino Data Lab

APRIL 7, 2019

If you are in research, excellent libraries like Allen NLP and NLP Architect are designed to make experimentation easier, although at the expense of feature completeness, speed and robustness. This article is intended to be a useful cheat sheet for narrowing down your choice. Not all open source NLP libraries are created equal.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

FineReport

DECEMBER 11, 2019

The article is interspersed with rich columns and pictures, introduces the basic business principles in a simple way with real cases from many companies and entrepreneurs around the world. – Data Divination: Big Data Strategies.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. It analyzes historical data and news articles, confirming a possible market correction.

Cost-Benefit 89

Cost-Benefit Modeling Manufacturing Interactive 89

Occam's Razor

AUGUST 22, 2011

" + Strategic Analysis Articles. Tactical Analysis Articles. Blogging Experience Articles. + Book Articles. Misc Articles. In each section the listing is from the latest article to the earliest. " Strategic Analysis Articles. Tactical Analysis Articles. How do I crush tough problems?

KPI 124

KPI Metrics Measurement ROI 124

Alation

SEPTEMBER 28, 2022

However, there is a lot more to know about DataOps, as it has its own definition, principles, benefits, and applications in real-life companies today – which we will cover in this article! Automated testing to ensure data quality. What Is DataOps? Easy-to-experiment data development environment. How Does DataOps Provide Value?

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

Occam's Razor

SEPTEMBER 19, 2011

Then they isolated regions of the country (by city, zip, state, dma pick your fave) into test and control regions. People in the test regions will participate in our hypothesis testing. So for variation #3, no catalogs or email were sent to the customers in the test group. The nice thing is that you can also test that!

Measurement 119

Measurement Advertising Testing Marketing 119

O'Reilly on Data

MAY 14, 2020

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. In this article, we shift our focus to the AI Product Manager’s skill set, as it is applied to day to day work in the design, development, and maintenance of AI products.

Management 363

Management Experimentation B2B Machine Learning 363

Domino Data Lab

AUGUST 5, 2019

The article focuses on 1) proposed frameworks for defining and designing for ethics and for understanding the forces that encourage industry to operationalize ethics, as well as 2) proposed ethical principles for data scientists to consider when developing data-empowered products. as well as consider the role of rights, harms, and justice.

Data Science 93

Data Science Data-driven Modeling Machine Learning 93

O'Reilly on Data

OCTOBER 19, 2021

In this article, we want to dig deeper into the fundamentals of machine learning as an engineering discipline and outline answers to key questions: Why does ML need special treatment in the first place? An Overarching Concern: Correctness and Testing. However, the concept is quite abstract. This approach is not novel.

IT 351

IT Testing Experimentation Software 351

The Unofficial Google Data Science Blog

JULY 22, 2020

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Insight

APRIL 28, 2020

In this article, we share some data-driven advice on how to get started on the right foot with an effective and appropriate screening process. Article by Adam Azzam. Originally posted on Open Data Science (ODSC). Teams new to hiring often make this mistake of creating long multi-stage screening processes.

Data-driven 53

Data-driven Data Science Experimentation Measurement 53

Insight

MARCH 12, 2020

In this article, I will discuss the construction of the AIgent, from data collection to model assembly. 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 In other words, if 0.1%

Modeling 59

Modeling Metadata Publishing Sales 59

Domino Data Lab

OCTOBER 2, 2019

This article covers causal relationships and includes a chapter excerpt from the book Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications by Andrew Kelleher and Adam Kelleher. As data science work is experimental and probabilistic in nature, data scientists are often faced with making inferences.

Machine Learning 68

Machine Learning Measurement Modeling Testing 68

O'Reilly on Data

OCTOBER 13, 2020

Our previous articles in this series introduce our own take on AI product management , discuss the skills that AI product managers need , and detail how to bring an AI product to market. In Bringing an AI Product to Market , we distinguished the debugging phase of product development from pre-deployment evaluation and testing.

Management 253

Management Metrics Machine Learning Modeling 253

CIO Business Intelligence

MARCH 7, 2023

I’ll be covering more examples of force multipliers in upcoming articles, and here are three to start that should apply to most CIOs and their IT organizations. Devops teams now look to shift left security and implement continuous testing to develop more innovative, secure, and reliable features from the start.

Digital Transformation 144

Digital Transformation Data Governance Experimentation Machine Learning 144

datapine

MAY 20, 2020

Finally, we will show you a real-life example so you can get a visual overview and a clearer picture of the points discussed in this article. When we say “optimal design,” we don’t mean cramming piles of information into one space or being overly experimental with colors. Test, tweak, evolve. Let’s begin.

Dashboards 265

Dashboards Reporting KPI Visualization 265

O'Reilly on Data

MARCH 23, 2023

It’s by far the most convincing example of a conversation with a machine; it has certainly passed the Turing test. Search and research Microsoft is currently beta testing Bing/Sydney, which is based on GPT-4. There’s the compute time, the engineering team—but there’s also the cost of verification, testing, and editing.

IT 271

IT Modeling Testing Risk 271

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

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

O'Reilly on Data

JULY 25, 2023

This article summarizes what I learned from that experience. The inspiration (and title) for it comes from Mike Loukides’ Radar article on Real World Programming with ChatGPT , which shares a similar spirit of digging into the potential and limits of AI tools for more realistic end-to-end programming tasks.

Consulting 246

Consulting Interactive Software IT 246

datapine

FEBRUARY 4, 2020

Below, in the article, we’ve gathered some of the marketing reports templates that can easily be used to perfect the efficiency of generating data and reduce the time needed to create it. As a Forbes article states , “there’s no such thing as ‘set it and forget it’ [in digital marketing]”. Use professional software.

Reporting 280

Reporting Marketing Advertising Metrics 280

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Introduction. Welcome back to our monthly burst of themes and conferences.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Perceptual Edge

AUGUST 26, 2019

A serious approach would begin with a thorough understanding of data visualization, which is not Pangilinan’s area of expertise, and would then proceed scientifically by designing and running experimental studies to test its usefulness. Her case is hollow.

Visualization 52

Visualization Cost-Benefit Interactive Experimentation 52

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. ” BTW, that Knuth article from 1983 was probably the first time that I ever saw the word “Web” used as a computer-related meaning. Introduction. BTW, videos for Rev2 are up: [link]. Software writes Software?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

only in enough detail to motivate the types of uncertainty that are central to this article. Should we use a t-test or a sign test? to run a brief experiment to test the hypothesis. It was now a business decision to decide whether to pursue this radical strategy given the projected hit to metrics. leaves out.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Domino Data Lab

AUGUST 26, 2019

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. This control prevents overfitting and reduction in predictive accuracy on new test data. 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

CIO Business Intelligence

FEBRUARY 9, 2024

Establish a corporate use policy As I mentioned in an earlier article , a corporate use policy and associated training can help educate employees on some risks and pitfalls of the technology, and provide rules and recommendations to get the most out of the tech, and, therefore, the most business value without putting the organization at risk.

IT 134

IT Experimentation Risk Testing 134

CIO Business Intelligence

APRIL 15, 2024

Given the speed required, Lowden established a specialized team for the project to encourage a culture of experimentation and “moving fast to learn fast.” “You The Tax Institute studies and analyzes the constantly shifting landscape of federal and state tax laws and publishes articles on how to deal with them.

Testing 78

Testing Experimentation Data Quality Machine Learning 78

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. This methodology of “test, look at the data, adjust” is at the heart and soul of business intelligence. Your Chance: Want to try a professional BI analytics software? Let’s look at our first use case.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214