IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Figure 1 illustrates the framework for Scope 3 emission estimation employing a large language model.

Experimentation 77

Experimentation Modeling Deep Learning Data-driven 77

AWS Big Data

JANUARY 9, 2024

Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications. Semantic search In semantic search, the search engine uses an ML model to encode text or other media (such as images and videos) from the source documents as a dense vector in a high-dimensional vector space.

Cost-Benefit 96

Cost-Benefit Visualization Modeling Machine Learning 96

IBM Big Data Hub

FEBRUARY 1, 2024

Today, more than 130 central banks are actively exploring CBDCs and publishing periodic reports on the functional and non-functional requirements of CBDC platforms, including the evolving architectural considerations and the outcomes of their various CBDC experimentations. Payment transaction privacy is also important.

Experimentation 95

Experimentation Modeling Finance Reporting 95

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. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 332

Management Machine Learning Experimentation Metrics 332

IBM Big Data Hub

DECEMBER 15, 2023

Open-source artificial intelligence (AI) refers to AI technologies where the source code is freely available for anyone to use, modify and distribute. This availability makes open-source projects and AI models popular with developers, researchers and organizations.

Deep Learning 67

Deep Learning Experimentation Machine Learning Risk 67

Dataiku

MARCH 25, 2024

This scenario is not science fiction but a glimpse into the capabilities of Multimodal Large Language Models (M-LLMs), where the convergence of various modalities extends the landscape of AI. M-LLMs for Image Captioning Image captioning refers to the process of automatically generating textual descriptions or captions for images.

Visualization 132

Visualization Modeling Experimentation Testing 132

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

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Rocket-Powered Data Science

JULY 7, 2019

Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…). Examples: Cars, Trucks, Taxis. See [link]. Industry 4.0 2) Connected cars. (3)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

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 116

Enterprise IT Experimentation Unstructured Data 116

IBM Big Data Hub

MARCH 4, 2024

We refer to this transformation as becoming an AI+ enterprise. Figure 2: ROI potential by transforming into an AI+ enterprise Organizations with high data maturity that embed an AI+ transformation model into the enterprise fabric and culture can generate up to 2.6 Consider the following: Do you need a public foundation model?

Enterprise 101

Enterprise ROI Risk Strategy 101

CIO Business Intelligence

DECEMBER 7, 2023

Over the last year, generative AI—a form of artificial intelligence that can compose original text, images, computer code, and other content—has gone from experimental curiosity to a tech revolution that could be one of the biggest business disruptors of our generation. Likewise, they realize that human talent will be central to success.

Insurance 72

Insurance Experimentation Finance Data Governance 72

DataRobot

MARCH 10, 2021

Deploy the machine learning model into production. The experimenters simulated experiences in online travel and online dating, varying the time people waited for a search result. The experimenters also varied whether the participants were shown the hidden work that the website was doing while they were waiting for results.

Experimentation 145

Experimentation Machine Learning Key Performance Indicator Reporting 145

Depict Data Studio

OCTOBER 26, 2021

This is referred to as “non-destructive” editing in the digital imaging world, and it is such a great feature for experimentation and creativity, because you risk nothing! It helps you – the presenter – organize and clarify your thoughts since they fit this visual model. Creating Cohesive Title Slides. Simple enough, right?

Visualization 116

Visualization Experimentation Software Strategy 116

Insight

MARCH 12, 2020

The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. Features: DistilBERT Text Embeddings Once I had a raw dataset, I could begin engineering features and building a natural language processing (NLP) model.

Modeling 59

Modeling Metadata Publishing Sales 59

CIO Business Intelligence

NOVEMBER 2, 2023

“Awareness of FinOps practices and the maturity of software that can automate cloud optimization activities have helped enterprises get a better understanding of key cost drivers,” McCarthy says, referring to the practice of blending finance and cloud operations to optimize cloud spend. It depends on what business model you’re in.

Strategy 138

Strategy Data Processing Experimentation Optimization 138

AWS Big Data

MAY 2, 2023

Removal of experimental Smart Sensors. This feature is particularly useful if you want to externally process various files, evaluate multiple machine learning models, or extraneously process a varied amount of data based on a SQL request. release highlights, refer to What’s New In Python 3.10. Apache Airflow v2.4.3 Airflow v2.4.0

Testing 105

Testing Experimentation Management Metadata 105

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. Most experts categorize it as a powerful, but narrow AI model.

Cost-Benefit 93

Cost-Benefit Modeling Manufacturing Interactive 93

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 71

Data Science Machine Learning Experimentation Cost-Benefit 71

Sisense

JULY 24, 2019

NLQ serves those users who are in a rush, or who lack the skills or permissions to model their data using visualization tools or code editors. Imagine a marine freight company using Captain Cook slang to refer to distances (fathom), weights (draft), and types of goods (treasures) being shipped across oceans.

Analytics 89

Analytics Experimentation Metadata Big Data 89

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

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. : Now every PG can be efficiently represented as an RDF model. This was already possible in the very first RDF 1.0 man :hasSpouse :woman.

Metadata 59

Metadata IT Modeling Experimentation 59

DataRobot Blog

JULY 28, 2022

Companies are emphasizing the accuracy of machine learning models while at the same time focusing on cost reduction, both of which are important. In addition to the accuracy of the models we built, we had to consider business metrics, cost, interpretability, and suitability for ongoing operations. Sensor Data Analysis Examples.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

The Unofficial Google Data Science Blog

JANUARY 16, 2018

Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. The graph of user collaboration can be separated into distinct connected components (hereafter referred to as "components"). We use hierarchical models for this effect.

Testing 58

Testing Experimentation Measurement Modeling 58

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

FineReport

DECEMBER 19, 2019

When it comes to data analysis, from database operations, data cleaning, data visualization , to machine learning, batch processing, script writing, model optimization, and deep learning, all these functions can be implemented with Python, and different libraries are provided for you to choose. From Google. Data Analysis Libraries.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Ontotext

NOVEMBER 2, 2023

However, it will take effort to formalize a shared semantic model that can be mapped to data assets, and turn unstructured data into a format that can be mined for insight. And while there is a great deal of experimentation underway, most organizations have only scratched the surface in a use-case-by-use-case fashion.

IT 69

IT Cost-Benefit Data-driven Technology 69

Cloudera

AUGUST 2, 2018

True – millions of credit card transactions are processed within minutes for consistency, fraud and compliance, using petabytes of historical transactions as reference data. Data teams in these insurance firms are leading the charge in rebuilding entire business models around data and analytics.

Data Warehouse 51

Data Warehouse Insurance Experimentation Software 51

Domino Data Lab

DECEMBER 4, 2020

NCA doesn’t require the assumption of a specific compartmental model for either drug or metabolite; it is instead assumption-free and therefore easily automated [1]. PharmaceUtical Modeling And Simulation (or PUMAS) is a suite of tools to perform quantitative analytics for pharmaceutical drug development [2]. References. [1]

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Ontotext

NOVEMBER 6, 2019

GraphDB Workbench is the interface for Ontotext’s semantic graph database, which provides the core infrastructure including modelling agility, data integration, relationship exploration and cross-enterprise semantic data publishing and consumption. The Plugins. The RDFRank plugin is one of the most popular plugins for GraphDB.

Experimentation 45

Experimentation Deep Learning Software Modeling 45

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. I've gone through the five stages in the Kubler-Ross model. We are headed towards having zero referring keywords from Google and, perhaps, other search engines.

Optimization 154

Optimization Reporting Experimentation Metrics 154

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

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 143

Cost-Benefit Metrics Insurance Measurement 143

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

Occam's Razor

APRIL 8, 2013

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. Another way to find the metric you want to change is to look at your business model. The business model also tells you what the metric should be.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

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

O'Reilly on Data

MARCH 23, 2023

It’s important to understand that ChatGPT is not actually a language model. It’s a convenient user interface built around one specific language model, GPT-3.5, is one of a class of language models that are sometimes called “large language models” (LLMs)—though that term isn’t very helpful. with specialized training.

IT 262

IT Modeling Testing Risk 262