Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. Organization: AWS Price: US$300 How to prepare: Amazon offers free exam guides, sample questions, practice tests, and digital training.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

CIO Business Intelligence

NOVEMBER 7, 2022

A developing playbook of best practices for data science teams covers the development process and technologies for building and testing machine learning models. CIOs and CDOs should lead ModelOps and oversee the lifecycle Leaders can review and address issues if the data science teams struggle to develop models.

Machine Learning 128

Machine Learning Data Science Experimentation IoT 128

Occam's Razor

MAY 22, 2006

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers.

Experimentation 103

Experimentation Testing Optimization Measurement 103

CIO Business Intelligence

JANUARY 9, 2024

That quote aptly describes what Dell Technologies and Intel are doing to help our enterprise customers quickly, effectively, and securely deploy generative AI and large language models (LLMs).Many We’re using our own databases, testing against our own needs, and building around specific problem sets.

Enterprise 118

Enterprise Experimentation Modeling Data-driven 118

CIO Business Intelligence

JUNE 28, 2023

Belcorp operates under a direct sales model in 14 countries. As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

Digital Transformation 104

Digital Transformation Cost-Benefit Informatics Data mining 104

CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. 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 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

MARCH 10, 2022

Fujitsu remains very much interested in the mainframe market, with a new model still on its roadmap for 2024, and a move under way to “shift its mainframes and UNIX servers to the cloud, gradually enhancing its existing business systems to optimize the experience for its end-users.”

Sales 129

Sales Testing Experimentation Data Processing 129

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 90

Cost-Benefit Modeling Manufacturing Interactive 90

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

CIO Business Intelligence

MARCH 7, 2023

OpenAI’s text-generating ChatGPT, along with its image generation cousin DALL-E, are the most prominent among a series of large language models, also known as generative language models or generative AI, that have captured the public’s imagination over the last year. And, he says, using generative AI for coding has worked well.

Enterprise 115

Enterprise IT Experimentation Unstructured Data 115

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. This has serious implications for software testing, versioning, deployment, and other core development processes.

Management 332

Management Machine Learning Experimentation Metrics 332

Cloudera

APRIL 9, 2021

Specifically, we’ll focus on training Machine Learning (ML) models to forecast ECC part production demand across all of its factories. This integration is key in assuring that models evolve with the data – to avoid, for example, model drift. A/B testing). model packaging, deployment and serving.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

IBM Big Data Hub

DECEMBER 14, 2023

Another year has passed—it felt like the whole world was talking about and trying out tools powered by generative AI and Large Language Models (LLMs). It is very easy to turn a terraform template into a deployable architecture and open the door to cost optimization, compliance management, self-service, standardization and repeatability.

Experimentation 73

Experimentation Testing Software Management 73

CIO Business Intelligence

OCTOBER 18, 2023

Of roughly 2,500 CIOs surveyed recently by Gartner, 9% say they have already deployed gen AI applications, and a staggering 55% say they will deploy large language models (LLMs) in production by the end of 2025. in concert with Microsoft’s AI-optimized Azure platform. John Spottiswood, COO of Jerry, a Palo Alto, Calif.-based

Risk 141

Risk Manufacturing Enterprise Technology 141

Octopai

OCTOBER 26, 2022

When DataOps principles are implemented within an organization, you see an increase in collaboration, experimentation, deployment speed and data quality. SPC is the continuous testing of the results of automated manufacturing processes. SPC tests can do the same thing for the data flowing through your pipelines.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

Occam's Razor

MARCH 23, 2021

This is very hard to do, we now have a proven seven-step experimentation process, with one of the coolest algorithms to pick matched-markets (normally the kiss of death of any large-scale geo experiment). The first component is a gloriously scaled global creative pre-testing program. Matched market tests. The slow music.

Analytics 131

Analytics Scorecard Strategy Testing 131

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. Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. But it is not routine.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. Capabilities Beyond Classic Jupyter for End-to-end Experimentation. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

Ontotext

MARCH 29, 2021

The authors of RDF-star proposed a new short syntax and because of its elegance, GraphDB optimized its persistence to nearly double the loading speed for dataset with lots of statement-level metadata. Now every PG can be efficiently represented as an RDF model. Ontotext: What is the significance of RDF-star?

Metadata 59

Metadata IT Modeling Experimentation 59

CIO Business Intelligence

JUNE 27, 2022

We rely heavily on automated testing. It’s not perfect by any means, and we are continuously breaking our own product, but it’s optimized for shipping new features to customers as quickly as we can. Tyson: That belief in your vision when it’s tested—that is tough! How do you get to that level of automation?

Software 114

Software Experimentation Testing Marketing 114

FineReport

DECEMBER 11, 2019

The big news is that we no longer need to be proficient in math or statistics, or even rely on expensive modeling software to analyze customers. – Data Divination: Big Data Strategies. Such huge amounts of data can help us better understand and predict customer behavior. Data analysis is setting off a revolution.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

Occam's Razor

SEPTEMBER 19, 2011

How do you get over the frustration of having done attribution modeling and realizing that it is not even remotely the solution to your challenge of using multiple media channels? We have to do Search Engine Optimization. Then they isolated regions of the country (by city, zip, state, dma pick your fave) into test and control regions.

Measurement 119

Measurement Advertising Testing Marketing 119

Occam's Razor

OCTOBER 21, 2013

As an analyst, I was upset that this change would hurt my ability to analyze the effectiveness of my beloved search engine optimization (SEO) efforts – which are really all about finding the right users using optimal content strategies. I've gone through the five stages in the Kubler-Ross model. silverlinings.

Optimization 154

Optimization Reporting Experimentation Metrics 154

O'Reilly on Data

OCTOBER 19, 2021

Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 346

IT Testing Experimentation Software 346

CIO Business Intelligence

APRIL 24, 2024

But to find ways it can help grow a company’s bottom line, CIOs have to do more to understand a company’s business model and identify opportunities where gen AI can change the playing field. We’re mostly still optimizing our sales and marketing processes with CRM tools,” he says. And hyper-personalization at scale.”

Sales 118

Sales Finance Experimentation Cost-Benefit 118

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

MAY 14, 2020

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

Management 363

Management Experimentation B2B Machine Learning 363

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. We offer two examples where this may be the case.

Experimentation 95

Experimentation Statistics Testing Strategy 95

DataKitchen

APRIL 13, 2021

Testing and Data Observability. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Testing and Data Observability.

Testing 307

Testing Machine Learning Consulting Data Quality 307

Occam's Razor

AUGUST 22, 2011

Key To Your Digital Success: Web Analytics Measurement Model. Web Data Quality: A 6 Step Process To Evolve Your Mental Model. Five Reasons And Awesome Testing Ideas. Lab Usability Testing: What, Why, How Much. Build A Great Web Experimentation & Testing Program. Experimentation and Testing: A Primer.

KPI 124

KPI Metrics Measurement ROI 124

O'Reilly on Data

MARCH 23, 2023

Many of these go slightly (but not very far) beyond your initial expectations: you can ask it to generate a list of terms for search engine optimization, you can ask it to generate a reading list on topics that you’re interested in. It’s important to understand that ChatGPT is not actually a language model. with specialized training.

IT 264

IT Modeling Testing Risk 264

Occam's Razor

AUGUST 12, 2013

than multi-channel attribution modeling. By the time you are done with this post you'll have complete knowledge of what's ugly and bad when it comes to attribution modeling. You'll know how to use the good model, even if it is far from perfect. Multi-Channel Attribution Models. Linear Attribution Model.

Modeling 161

Modeling Optimization Marketing Interactive 161

Occam's Razor

DECEMBER 9, 2009

The four pronged real world tested probing and loaded with politics framework to find a home for Web Analytics: 1. some reports going out on schedule (even if data pukes) then an optimal path might be to centralize some where (see item #2 below). [B] Which physical organizational model will work best for you? Centralized?

Analytics 95

Analytics Data-driven Marketing Sales 95

Cloudera

MARCH 2, 2022

You can read previous blog posts on Impala’s performance and querying techniques here – “ New Multithreading Model for Apache Impala ”, “ Keeping Small Queries Fast – Short query optimizations in Apache Impala ” and “ Faster Performance for Selective Queries ”. . Analytical SQL workloads use aggregates and joins heavily.

Data Warehouse 85

Data Warehouse Optimization Analytics Sales 85

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

CIO Business Intelligence

MAY 1, 2024

Gen AI takes us from single-use models of machine learning (ML) to AI tools that promise to be a platform with uses in many areas, but you still need to validate they’re appropriate for the problems you want solved, and that your users know how to use gen AI effectively. Pilots can offer value beyond just experimentation, of course.

Cost-Benefit 52

Cost-Benefit Metrics Insurance Measurement 52