Data Science 101

SEPTEMBER 1, 2023

I remember helping with my school website and also working on several WordPress blogs for myself and friends/family. If I had more room for experimentation though, I’d definitely give svelte and solidjs a try. I’ve been tinkering around with the web since I started learning how to code way back in high school.

Experimentation 116

Experimentation Testing Technology IT 116

The Unofficial Google Data Science Blog

JANUARY 16, 2018

We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. This simulation is based on the actual user network of GCP.

Testing 58

Testing Experimentation Measurement Modeling 58

Cloudera

OCTOBER 18, 2023

In fact, some of the insights presented in this blog have been assisted by the power of large language models (LLMs), highlighting the synergy between human expertise and AI-driven insights. Testing: Generative AI can be used to generate test cases automatically, reducing the time and effort required for developers to test their code.

Cost-Benefit 77

Cost-Benefit Testing Machine Learning Optimization 77

DataKitchen

JANUARY 20, 2021

Develop/execute regression testing . Test data management and other functions provided ‘as a service’ . A COE typically has a full-time staff that focuses on delivering value for customers in an experimentation-driven, iterative, result-oriented, customer-focused way. Agile ticketing/Kanban tools. Deploy to production.

Metrics 243

Metrics Experimentation Measurement Testing 243

Decision Management Solutions

MARCH 26, 2020

We’ve been blogging recently on Decision Optimization. Randomly select groups of customers and use the experimental approach on them, to prevent bias, and ensure a clean test Keep information on both groups – what you would normally do and what you experimented on – so you can compare the approaches later.

Experimentation 72

Experimentation Recreation/Entertainment Optimization Testing 72

Smart Data Collective

JUNE 29, 2022

It could be a helpful blog post, an insightful whitepaper, or just a quick tip. Test Different Calls-to-Action. You will need to test different CTAs, which is going to require data analytics tools. Test Different Professional Email Signature. You should also use data analytics to test different email signatures.

B2B 108

B2B Data-driven Marketing Strategy 108

The Unofficial Google Data Science Blog

APRIL 23, 2024

This blog post discusses such a comprehensive approach that is used at Youtube. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. And we can keep repeating this approach, relying on intuition and luck.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Dataiku

MARCH 25, 2024

In this blog post, we delve into the workings of M-LLMs, unraveling the intricacies of their architecture, with a particular focus on text and vision integration. One limitation observed while testing the LENS approach, particularly in VQA, is its heavy reliance on the output of the first modules, namely CLIP and BLIP captions.

Visualization 132

Visualization Modeling Experimentation Testing 132

Domino Data Lab

MAY 15, 2019

While the talk provides both organizational foundations for machine learning as well as product management insights to consider when shipping ML projects, I will be focusing on the latter in this blog post. These steps also reflect the experimental nature of ML product management. more probabilistic rather than deterministic).

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

IBM Big Data Hub

DECEMBER 14, 2023

The extension of the CIO office’s dedicated data center to the IBM public cloud allowed for experimentation and growth with zero risk. The Terraform automation and automated regression testing allowed me to reliably change the connection mechanism from direct link to VPN. Automated regression tests are a dynamite.

Experimentation 75

Experimentation Testing Software Management 75

Smarten

MAY 17, 2023

Create a Sandbox Environment If you are in the business of technology, you probably have a robust sandbox environment in which you can use new tools and leverage opportunities with test data to understand the value of tools like Azure OpenAI, GPT 3.x

Digital Transformation 52

Digital Transformation Experimentation Risk Testing 52

IBM Big Data Hub

NOVEMBER 3, 2023

Knowing this, we designed IBM Event Automation to make event processing easy with a no-code approach to Apache Flink It gives you the ability to quickly test new ideas, reuse events to expand into new use cases, and help accelerate your time to value.”

Cost-Benefit 79

Cost-Benefit Experimentation Testing Digital Transformation 79

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. Issue detected? This means that more focused development can happen faster. .

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

Domino Data Lab

JUNE 13, 2019

Recently, Chhavi Yadav (NYU) and Leon Bottou (Facebook AI Research and NYU) indicated in their paper, “ Cold Case: The Lost MNIST Digits ”, how they reconstructed the MNIST (Modified National Institute of Standards and Technology) dataset and added 50,000 samples to the test set for a total of 60,000 samples. Did they overfit the test set?

Testing 83

Testing Data Science Experimentation Metadata 83

Cloudera

APRIL 9, 2021

This is part 4 in this blog series. This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The second blog dealt with creating and managing Data Enrichment pipelines. A/B testing).

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

A/B testing is used widely in information technology companies to guide product development and improvements. For questions as disparate as website design and UI, prediction algorithms, or user flows within apps, live traffic tests help developers understand what works well for users and the business, and what doesn’t.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

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

Ontotext

FEBRUARY 14, 2024

With things like named graphs, layering the data, testing those what-if scenarios, and checking the state is fantastic. We find that as great as SHACL is at ensuring the data quality, testing the RDF pipelines is another matter. Experimentation is important, but be explicit when you do. How do you do that? Start with “why?”

Recreation/Entertainment 105

Recreation/Entertainment Data Integration Modeling Data Quality 105

Alation

DECEMBER 20, 2022

These organizations use experimentation and constant market testing to learn and invest. Subscribe to Alation's Blog. The change can fail and reveal insights into the organization that leads to better future transformation.” Parting Words. Successful digital transformation requires more than avoiding the above pitfalls.

Digital Transformation 96

Digital Transformation Scorecard Measurement Experimentation 96

CIO Business Intelligence

AUGUST 17, 2023

We’re testing ChatGPT at an individual level,” he says. In general, we see a small number of organizations using generative AI based on a strategy or plan, shaped by clear policies, and a lot of grassroots experimentation, but that’s almost always happening in a strategy vacuum.” Medica’s O’Brien issues a caution as well.

Risk 98

Risk Cost-Benefit Strategy Experimentation 98

Data Science and Beyond

APRIL 5, 2021

I summarised this work in a post on the company’s blog , and discussed it in an interview with PublishPress. My main "day job" focus in 2020 was on being the tech lead for Automattic’s new experimentation platform (ExPlat). This aligns well with my long-standing interest in causal inference.

Experimentation 61

Experimentation Testing Publishing Measurement 61

Depict Data Studio

JULY 13, 2021

a school district’s worth of students), it’s still unlikely you need statistics, unless you are trying to answer a scientific-type question (and what scientific-type questions nonprofits with a lot of data might ask is for another blog post on another day). Even if you have more people than that (e.g., Ask us more about Data Teams!

Statistics 98

Statistics Testing Recreation/Entertainment Experimentation 98

The Data Visualisation Catalogue

MARCH 3, 2019

This experimental visualisation uses a polar layout and extends into into 3D with a cylindrical form. A spherical variation was also tested out: Source: The Design Space of Implicit Hierarchy Visualization: A Survey, p. A spherical variation was also tested out: Source: The Design Space of Implicit Hierarchy Visualization: A Survey, p.

Experimentation 40

Experimentation Visualization Testing IT 40

Smarten

APRIL 18, 2023

While new medical techniques and tools can take time to refine and prove, doctors often leverage experimental techniques to save lives. It does not accommodate images and its security compliance has yet to be thoroughly tested. As these techniques are refined, they enter into the mainstream and become more common place.

Digital Transformation 52

Digital Transformation Experimentation ROI Technology 52

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

Domino Data Lab

AUGUST 6, 2021

Develop: includes accessing and preparing data and algorithms, researching and development of models and experimentation. During this part of development, data scientists begin creating models and conducting experiments to test their performance. The Deploy phase is where the tested model is transferred to a production environment.

Data Science 75

Data Science Testing Modeling Publishing 75

Dataiku

APRIL 22, 2022

In this blog series, we will explore Frugal AI from the perspectives of data, design, trust, and sustainability. For companies with small datasets and a mandate to move beyond experimentation, Frugal AI promises to be a way to overcome this challenge. It's All in a Name. Today, in 2022, the code (i.e.,

Experimentation 59

Experimentation Modeling Business Objectives Manufacturing 59

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. This personalized approach might lead to more effective therapies with fewer side effects.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

Cloudera

JANUARY 30, 2019

Data scientists require on-demand access to data, powerful processing infrastructure, and multiple tools and libraries for development and experimentation. Run experiments with historical reference for hyperparameter tuning, feature engineering, grid searches, A/B testing and more. Sound familiar?

Data Science 73

Data Science Machine Learning Experimentation Cost-Benefit 73

Domino Data Lab

AUGUST 6, 2021

The process of doing data science is about learning from experimentation failures, but inadvertent errors can create enormous risks in model implementation. Outputs for a new problem might not be consistent with the model’s original intent for a different problem without careful research and testing. Model implementation.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

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

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. Image Credit: Parsa Ghaffari on the Raylien Blog. These can be either classical or deep-learning-based pipelines.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

Occam's Razor

AUGUST 22, 2011

Here you'll find all my blog posts categorized into a structure that will hopefully make it easy for you to discover new content, find answers to your questions, or simply wallow in some excellent analytics narratives. Blogging Experience Articles. + Podcast: Measuring Rich Media (Ajax, Flash / Flex, RSS & Blogs).

KPI 124

KPI Metrics Measurement ROI 124

Cloudera

AUGUST 2, 2018

Today, we are announcing Cloudera Data Warehouse – our battle-tested modern data warehousing solution – formerly known as Cloudera Analytic DB. Watch for more blogs to come on this topic as we work with you to continuously innovate and transform the industry – with modern data warehousing.

Data Warehouse 51

Data Warehouse Insurance Experimentation Software 51

Cloudera

FEBRUARY 16, 2022

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. The post Of Muffins and Machine Learning Models appeared first on Cloudera Blog.

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

Domino Data Lab

NOVEMBER 14, 2019

advocate for “defining interpretability in the context of machine learning” and for using a Predictive, Descriptive, Relevant (PDR) framework because there is “considerable confusion about the notion of interpretability” Data science work is experimental, iterative, and at times, confusing.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

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. Technical environments and IDEs must be disposable so that experimental costs can be kept to a minimum. Simplicity.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52