Analytics Vidhya

MARCH 22, 2024

Introduction With the advent of RAG (Retrieval Augmented Generation) and Large Language Models (LLMs), knowledge-intensive tasks like Document Question Answering, have become a lot more efficient and robust without the immediate need to fine-tune a cost-expensive LLM to solve downstream tasks.

Modeling 167

Modeling Analytics Metadata 167

Analytics Vidhya

SEPTEMBER 24, 2023

Introduction In the world of information retrieval, where oceans of text data await exploration, the ability to pinpoint relevant documents efficiently is invaluable. Traditional keyword-based search has its limitations, especially when dealing with personal and confidential data.

Analytics 328

Analytics IT Modeling 328

Analytics Vidhya

MAY 5, 2023

A researcher within Google leaked a document on a public Discord server recently. There is much controversy surrounding the document’s authenticity. But what interests people most is […] The post Google Afraid of Open-Source Community Outpacing Tech Giants in Language Model Race appeared first on Analytics Vidhya.

Modeling 312

Modeling Analytics IT Technology 312

Analytics Vidhya

JULY 20, 2022

Introduction Training and inference with large neural models are computationally expensive and time-consuming. While new tasks and models emerge so often for many application domains, the underlying documents being modeled stay mostly unaltered. In light of this, to improve the efficiency of future […].

Modeling 342

Modeling Data Science Publishing Analytics 342

Analytics Vidhya

JULY 27, 2023

Introduction A highly effective method in machine learning and natural language processing is topic modeling. A corpus of text is an example of a collection of documents. This technique involves finding abstract subjects that appear there.

Modeling 264

Modeling Machine Learning Analytics 264

Analytics Vidhya

APRIL 1, 2024

In this hands-on guide, we explore creating a sophisticated Q&A assistant powered by LLamA2 and LLamAIndex, leveraging state-of-the-art language models and indexing frameworks to navigate a sea of PDF documents effortlessly.

Machine Learning 292

Machine Learning Interactive Modeling Analytics 292

CIO Business Intelligence

OCTOBER 11, 2022

Google on Tuesday said it was updating its AI agent-based technology to add an enterprise-scale translation service, and to further automate document processing. . The Translation Hub, according to the company, is an AI agent-based service that offers self-service document translation with support for 135 languages.

Enterprise 128

Enterprise Technology Management Modeling 128

Analytics Vidhya

FEBRUARY 3, 2022

This article will provide you with a hands-on implementation on how to deploy an ML model in the Azure cloud. If you are new to Azure machine learning, I would recommend you to go through the Microsoft documentation that has been provided in the […].

Modeling 318

Modeling Machine Learning Data Science Publishing 318

BA Learnings

MARCH 8, 2020

Creating a procedure document that users can follow thus becomes a key activity for business analysts that needs to be completed so that system users can perform their duties using the new system or process on day one. Are you looking to create a procedure document?

Visualization 147

Visualization Software Modeling IT 147

Timo Elliott

MAY 11, 2023

Large-language models are going to fundamentally change how we create and consume documents in an era where everybody will be getting information via chatbots. Looking to the future, what’s the point of documents? I have to spend a lot of time reviewing information to try to stay abreast of current trends. and should it?)

Marketing 105

Marketing Optimization Publishing Modeling 105

KDnuggets

FEBRUARY 3, 2022

Transformer based language models such as BERT are really good at understanding the semantic context because they were designed specifically for that purpose. How can we use BERT to classify long text documents? BERT outperforms all NLP baselines, but as we say in the scientific community, “no free lunch”.

Modeling 110

Modeling 110

Analytics Vidhya

NOVEMBER 3, 2023

Introduction The field of artificial intelligence has seen remarkable advancements in recent years, particularly in the area of large language models. LLMs can generate human-like text, summarize documents, and write software code.

Modeling 307

Modeling Software Analytics IT 307

Analytics Vidhya

NOVEMBER 3, 2023

Introduction Question and answering on custom data is one of the most sought-after use cases of Large Language Models. Human-like conversational skills of LLMs combined with vector retrieval methods make it much easier to extract answers from large documents.

Interactive 283

Interactive Modeling Analytics IT 283

Analytics Vidhya

OCTOBER 1, 2023

Introduction Before the large language models era, extracting invoices was a tedious task. For invoice extraction, one has to gather data, build a document search machine learning model, model fine-tuning etc. The introduction of Generative AI took all of us by storm and many things were simplified using the LLM model.

Machine Learning 326

Machine Learning Modeling Analytics Data Science 326

Analytics Vidhya

FEBRUARY 21, 2024

In a bid to revolutionize the way users engage with PDF documents, Adobe has rolled out an innovative AI assistant feature embedded within its Reader and Acrobat applications.

Analytics 277

Analytics IT Modeling 277

Analytics Vidhya

JANUARY 23, 2024

Introduction Imagine standing in a dimly lit library, struggling to decipher a complex document while juggling dozens of other texts. Limitations of RNNs Traditional sequential models, like Recurrent Neural Networks (RNNs), processed language […] The post What are the Different Types of Attention Mechanisms?

Modeling 287

Modeling Analytics Deep Learning IT 287

Analytics Vidhya

JUNE 21, 2023

The adaptability of transformers makes these models invaluable for handling various document formats. Extracting critical information from PDFs is vital today, and transformers offer an efficient solution for automating PDF summarization. Applications span industries like law, finance, and academia.

Finance 265

Finance Modeling Analytics Data Science 265

IBM Big Data Hub

FEBRUARY 22, 2024

The rise of foundation models that power the growth of generative AI and other AI use cases offers exciting possibilities—yet it also raises new questions and concerns about their ethical design, development, deployment, and use. Emerging risks intrinsic to foundation models and their inherent generative capabilities.

Modeling 68

Modeling Risk Strategy Enterprise 68

CIO Business Intelligence

NOVEMBER 16, 2023

A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. But there’s a problem with it — you can never be sure if the information you upload won’t be used to train the next generation of the model. And yes, they’re working.”

Modeling 139

Modeling Enterprise Marketing Sales 139

Analytics Vidhya

AUGUST 9, 2020

Overview Learn about Information Retrieval (IR), Vector Space Models (VSM), and Mean Average Precision (MAP) Create a project on Information Retrieval using word2vec based. The post Information Retrieval using word2vec based Vector Space Model appeared first on Analytics Vidhya.

Modeling 290

Modeling Analytics Unstructured Data 290

erwin

FEBRUARY 12, 2021

Shockingly, a lot of organizations, even today, manage this through, either homemade tools or documents, checklists, Excel files, custom-made databases and so on and so forth. Traditionally, these are manually documented, monitored and managed. Everything needs to be clearly documented, covering all important and relevant aspects.

Risk 98

Risk Slice and Dice Management Enterprise 98

erwin

MAY 2, 2022

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative. Data modeling basics.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

O'Reilly on Data

DECEMBER 12, 2023

If the output of a model can’t be owned by a human, who (or what) is responsible if that output infringes existing copyright? In an article in The New Yorker , Jaron Lanier introduces the idea of data dignity, which implicitly distinguishes between training a model and generating output using a model.

Modeling 251

Modeling Software Sales Statistics 251

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States.

Risk 64

Risk Modeling Machine Learning Data Quality 64

Analytics Vidhya

SEPTEMBER 29, 2023

From research papers in PDF to reports in DOCX and plain text documents (TXT), to structured data in CSV files, there’s […] The post How to Develop A Multi-File Chatbot? appeared first on Analytics Vidhya.

Structured Data 322

Structured Data Data-driven Reporting Analytics 322

IBM Big Data Hub

SEPTEMBER 12, 2023

The UK government’s Ecosystem of Trust is a potential future border model for frictionless trade, which the UK government committed to pilot testing from October 2022 to March 2023. The models also reduce private sector customs data collection costs by 40%.

Testing 94

Testing Modeling Cost-Benefit Consulting 94

Domino Data Lab

JULY 14, 2022

The financial services industries are starting to realize the full import of the fact that, like household chores like dishwashing and garden work, ML models are never really done. Rather, AI and ML models need to be monitored for validity, and often, they also need to be re-explained and re-documented for regulators.

Insurance 98

Insurance Modeling Management Risk Management 98

erwin

MARCH 17, 2020

Teams need to urgently respond to everything from massive changes in workforce access and management to what-if planning for a variety of grim scenarios, in addition to building and documenting new applications and providing fast, accurate access to data for smart decision-making. Enterprise Architecture & Business Process Modeling.

Data Governance 138

Data Governance Enterprise Modeling Metadata 138

Decision Management Solutions

MAY 12, 2021

by Charlotte DeKeyrel, Expert Decision Modeler. When decisions are properly documented and developed with rigor, everyone gets smarter by understanding the complexities and flow of decision-making. The post Raise Your Corporate IQ by Documenting and Sharing Business Knowledge appeared first on Decision Management Solutions.

Experimentation 52

Experimentation Modeling Insurance Management 52

O'Reilly on Data

OCTOBER 30, 2023

While I am heartened to hear that the Executive Order on AI uses the Defense Production Act to compel disclosure of various data from the development of large AI models, these disclosures do not go far enough. These include: What data sources the model is trained on. Operational Metrics. Energy usage and other environmental impacts.

Measurement 296

Measurement Risk Modeling Metrics 296

erwin

JULY 2, 2020

Users discuss how they are putting erwin’s data modeling, enterprise architecture, business process modeling, and data intelligences solutions to work. IT Central Station members using erwin solutions are realizing the benefits of enterprise modeling and data intelligence. They have documented 200 business processes in this way.

Enterprise 122

Enterprise Modeling Metadata Data Governance 122

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 77

Risk Modeling Management Metadata 77

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. When business decisions are made based on bad models, the consequences can be severe. As machine learning advances globally, we can only expect the focus on model risk to continue to increase.

Risk 111

Risk Modeling IT Risk Management 111

Analytics Vidhya

AUGUST 18, 2023

Introduction In a world filled with information, PDF documents have become a staple for sharing and preserving valuable data. However, extracting insights from PDFs hasn’t always been straightforward. That’s where “Chat with PDFs” comes to the rescue – an innovative project revolutionising how we interact with PDFs.

Interactive 270

Interactive Analytics Modeling 270

Analytics Vidhya

APRIL 15, 2024

RAG is what is necessary for the Large Language Models (LLMs) to provide or generate accurate and factual answers. Introduction Retrieval Augmented-Generation (RAG) has taken the world by Storm ever since its inception.

Modeling 330

Modeling Analytics IT 330

Domino Data Lab

AUGUST 6, 2021

All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards. As such, model governance needs to be applied to each model for as long as it’s being used. What Is Model Governance?

Machine Learning 145

Machine Learning Modeling Testing Risk 145