Dataiku

MARCH 30, 2022

The last 20 years have seen staggering advancements in the field of Natural Language Processing (NLP). It used to be that “performing text analysis” meant reading hundreds of individual comments or documents to manually tag them and identify sentiment and key themes.

Machine Learning 98

Machine Learning Modeling IT 98

Ontotext

APRIL 19, 2024

Image by Gerd Altmann from Pixabay Assisted annotation and other automation methods that can be used for knowledge graph creation and natural language understanding should be more flexible and iterative than they often are. But Ontotext has been investing for over 20 years in the area of natural language processing (NLP) as well.

Metadata 52

Metadata Statistics Interactive Enterprise 52

CIO Business Intelligence

SEPTEMBER 29, 2023

Natural language processing (NLP) Natural language processing (NLP) technology helps computers better understand human language to improve chatbots, AI assistants, automation, and other tasks. Language is constantly evolving, with nuances that can make AI-generated conversations feel unnatural, confusing, or robotic.

Deep Learning 142

Deep Learning Machine Learning Modeling Consulting 142

CIO Business Intelligence

OCTOBER 24, 2023

The capabilities of these new generative AI tools, most of which are powered by large language models (LLM), forced every company and employee to rethink how they work. Vector Databases To make use of a Large Language Model, you’re going to need to vectorize your data. For that, you’ll need an embedding model.

Cost-Benefit 118

Cost-Benefit Modeling Data Quality Statistics 118

CIO Business Intelligence

JANUARY 13, 2023

The tool, which is built on Google’s Vertex AI Vision and powered by two machine learning models — product recognizer and tag organizer — can be used to identify different product types based on visual imaging and text features, the company said, adding that retailers don’t have to spend time and effort into training their own AI models.

Machine Learning 120

Machine Learning Sales Optimization Modeling 120

AWS Big Data

OCTOBER 10, 2023

In this post, we showcase how to use AWS Glue with AWS Glue Data Quality , sensitive data detection transforms , and AWS Lake Formation tag-based access control to automate data governance. For the purpose of this post, the following governance policies are defined: No PII data should exist in tables or columns tagged as public.

Data Quality 89

Data Quality Data Governance Data Lake Testing 89

O'Reilly on Data

MARCH 7, 2019

We’re in an exciting decade for natural language processing (NLP). Computers will get as good as humans in complex tasks like reading comprehension, language translation, and creative writing. Meet the language of emergency room triage notes. Yes, emergency rooms have their own language. are written in English.

Deep Learning 227

Deep Learning Testing Machine Learning Modeling 227

Ontotext

MARCH 13, 2024

OTKG models information about Ontotext, combined with content produced by different teams inside the organization. Our standard methodology for such projects is to start by defining competency questions that would help us understand what we need to model in our graph. This is graph-based tagging, so the mentions are not just keywords.

Marketing 72

Marketing Knowledge Discovery Metadata Data-driven 72

IBM Big Data Hub

APRIL 18, 2024

AI systems like LaMDA and GPT-3 excel at generating human-quality text, accomplishing specific tasks, translating languages as needed, and creating different kinds of creative content. Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles.

Cost-Benefit 87

Cost-Benefit Modeling Manufacturing Interactive 87

Ontotext

FEBRUARY 1, 2024

We as a taxonomy community are facing rapid technological change and grappling with where our discipline fits into a world captivated by ChatGPT and other generative models. The challenge of complexity Knowledge models for taxonomy have responded to an increasing need for sophistication and expressiveness.

Enterprise 59

Enterprise Management Metadata Modeling 59

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. That’s incredibly powerful.”

Enterprise 110

Enterprise IT Experimentation Unstructured Data 110

CIO Business Intelligence

APRIL 24, 2024

Many see the high price tag of initial offerings and a lack of understanding as to how workflows will need to be adjusted to truly capture the value of copilots as deterrents to signing on for the added functionality. The announcement comes amid reluctance among some CIOs regarding the ROI of generative AI copilots.

Enterprise 73

Enterprise Digital Transformation Consulting Risk 73

Ontotext

NOVEMBER 28, 2023

The aim of the project is to help PAs detect and analyze disinformation from multiple online sources, modalities, and languages. The data to be stored comes from multiple sources, modalities and languages. Similarly, the data model has to support multiple modalities, including text, audio, image, video, etc.

Modeling 59

Modeling Reporting IT 59

Insight

MARCH 12, 2020

Using nothing more than a book’s synopsis, the AIgent can surface similar books, genre tags, and sales proxies. 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) and metadata (i.e.

Modeling 59

Modeling Metadata Publishing Sales 59

Ontotext

JULY 13, 2023

Knowledge graphs have greatly helped to successfully enhance business-critical enterprise applications, especially those where high performance tagging and agile data integration is needed. The customer and employee experience when using an application is key for companies to have a real impact on their processes and results.

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

CIO Business Intelligence

JANUARY 15, 2024

In its Predictive Demand Planning solution, SAP is using a self-learning model to provide longer-range forecasts, alert users to the root causes of forecast changes, and make recommendations. Such capabilities are part of its Industry Cloud family of products, and can be integrated with any ERP system, not just SAP’s.

Sales 89

Sales Software Forecasting Statistics 89

AWS Big Data

NOVEMBER 17, 2023

For more information, refer SQL models. Tests – These are assertions you make about your models and other resources in your dbt project (such as sources, seeds, and snapshots). They are analogous to “functions” in other programming languages, and are extremely useful if you find yourself repeating code across multiple models.

Snapshot 89

Snapshot Data Processing Testing Data Warehouse 89

IBM Big Data Hub

OCTOBER 16, 2023

Voice-based queries use Natural Language Processing (NLP) and sentiment analysis for speech recognition. One bank using a watsonx Assistant system for customer service found the chatbot answered 96% of all customer questions correctly, quickly, consistently, and in multiple languages. Many stock market transactions use ML.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data. What is text mining?

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

Smart Data Collective

APRIL 10, 2020

This is achieved through natural language processing. Artificial intelligence models also improve the visual elements of these search results. eCommerce software with AI automatically tags, organizes and visually searches content using advanced labeling features. Automated logistics systems improve warehouse efficiency.

Sales 143

Sales Visualization Marketing Software 143

Ontotext

FEBRUARY 14, 2024

It has been an important capability for Ontotext ever since we dove into Natural Language Processing (NLP), as it is a crucial aspect of the interplay between text analysis and knowledge graphs. One such example is the tagging behind News On the Web. Out of the box, the model links to Wikidata IDs.

Cost-Benefit 52

Cost-Benefit Modeling Metadata Optimization 52

IBM Big Data Hub

FEBRUARY 14, 2024

Voice-based queries use natural language processing (NLP) and sentiment analysis for speech recognition so their conversations can begin immediately. Not only will this help scale the AOT tech across markets, but it will also help tackle integrations including additional languages, dialects and menu variations.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. These data models predict outcomes of new data. Programming Language (R or Python). Programming knowledge is needed for the typical tasks of transforming data, creating graphs, and creating data models. For academics and domain experts, R is the preferred language.

Data Science 104

Data Science Statistics Deep Learning Machine Learning 104

Cloudera

JUNE 26, 2023

For data engineering teams, Airflow is regarded as the best in class tool for orchestration (scheduling and managing end-to-end workflow) of pipelines that are built using programming languages like Python and SPARK. Impala vs Spark Use Impala primarily for analytical workloads triggered by end users.

Testing 76

Testing Data Processing Visualization Data Science 76

Sisense

JANUARY 8, 2021

Yik Yak could have tagged message content with the originating IP address and then quickly blocked messages from that IP after abusive language was detected. Leveraging the right collective datasets with CNNs could have identified images tagged to a geographical place already freely shared on the internet.

Cost-Benefit 98

Cost-Benefit Forecasting Data Lake Data-driven 98

AWS Big Data

FEBRUARY 29, 2024

Working with large language models (LLMs) for enterprise use cases requires the implementation of quality and privacy considerations to drive responsible AI. Enterprises are doing this by using proprietary data with approaches like Retrieval Augmented Generation (RAG), fine-tuning, and continued pre-training with foundation models.

Data Governance 93

Data Governance Unstructured Data Metadata Data Lake 93

Sisense

APRIL 30, 2020

In Talking Data , we delve into the rapidly evolving worlds of Natural Language Processing and Generation. Text data is proliferating at a staggering rate, and only advanced coding languages like Python and R will be able to pull insights out of these datasets at scale. Begin by removing the URLs and HTML tags. get_text().

Machine Learning 91

Machine Learning Statistics Modeling IT 91

Rocket-Powered Data Science

MARCH 10, 2020

And this: perhaps the most powerful node in a graph model for real-world use cases might be “context”. How does one express “context” in a data model? After all, the standard relational model of databases instantiated these types of relationships in its very foundation decades ago: the ERD (Entity-Relationship Diagram).

Metadata 250

Metadata Machine Learning ROI Prescriptive Analytics 250

Cloudera

DECEMBER 21, 2020

He downloads the Cloudera Fast Forward report about modeling Telco Churn and after reading it, his interest is piqued. Shaun plans to clone the exemplified model linked from the report to his local environment. He is particularly excited about model interpretability: Refractor and desires to experiment with this project on his own. .

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

Jet Global

APRIL 2, 2019

Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. How should data be tagged, sorted, grouped, and analyzed? By using Structured Query Language, or SQL, the language used to manipulate and extract data stored in cubes.

Enterprise 80

Enterprise OLAP Business Intelligence Internet of Things 80

CIO Business Intelligence

MAY 3, 2022

A strong governance plan that includes best practices like tagging, workload management, RACI [responsible, accountable, consulted, and informed] matrix , rightsizing, cost management, security monitoring, etc., In our case, the strategy is migrating to a cloud-based secure access service edge and zero-trust service model.”.

Management 143

Management Scorecard Cost-Benefit Risk 143

DataRobot

JUNE 9, 2021

This often unduly increases model pipeline complexity, with major nuances being the pulling and shifting of data from where your data lives in production databases and handing machine learning operations teams a series of model artifacts with dependencies that need to be reassembled to put that model into production.

Machine Learning 52

Machine Learning Modeling Data Processing 52

Insight

NOVEMBER 14, 2019

To prepare the data for topic modeling, I tokenized (split the document into sentences and sentences into words), removed punctuation and made them lower-case. Part of Speech (POS) Tagging After LDA, I decided to tag the part of speech (POS) for each reflection and extract the verbs. Jagarlamudi, H. Daume III and R.

Testing 54

Testing Modeling Strategy Interactive 54

Smart Data Collective

FEBRUARY 15, 2022

As a result, they can index countless web pages that don’t have the “nocrawl” attribute in their meta tags. They are also coming up with new models that reduce the risk of false positives. First, they often included strings of text that were widespread phrases in the English language.

Machine Learning 115

Machine Learning Deep Learning Software Technology 115

Ontotext

MAY 26, 2021

As Wikipedia is not only the biggest encyclopedia, but its contributors adhere to a strict editorial process, each industry tag is usually assigned by one person and reviewed by another. Gold Standards are also needed to create training and evaluation sets for AI systems when we want to extract information from free text.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

CIO Business Intelligence

SEPTEMBER 12, 2023

They conjure mistakes out of thin air There’s something almost magical about the way large language models (LLMs) write 1,000-word essays on obscure topics like the mating rituals of sand cranes or the importance of crenulations in 17th century Eastern European architecture. We saw the same thing happen with services like Uber.

Enterprise 117

Enterprise Consulting Technology IT 117

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. As with the part 1 and part 2 of this data modeling blog series, the cloud is not nirvana. Data modeling basics. Data Modeling. This blog is based upon a recent webcast that can be viewed here.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52