PyImageSearch

DECEMBER 16, 2024

It has been trained on diverse datasets that contain both visual and textual elements, making it versatile for tasks such as visual question answering, document understanding, image captioning, etc. But What Is Document Understanding? In Figure 1 , we can see the architecture of PaliGemma.

Deep Learning 104

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Analytics Vidhya

NOVEMBER 21, 2023

The vector stores have become an integral part of developing apps with Deep Learning Models, especially the Large Language Models. In the ever-evolving landscape of […] The post A Deep Dive into Qdrant, the Rust-Based Vector Database appeared first on Analytics Vidhya.

Database 319

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Data Science Dojo

JULY 2, 2023

Transformers, a type of Deep Learning model, have played a crucial role in the rise of LLMs. This solution aims to address the deep learning deployment gap in the banking sector by jump-starting banks’ deep learning language capabilities in a matter of weeks, rather than years [ 1 ].

Natural Language Processing 369

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Flipboard

MARCH 17, 2025

This makes it ideal for high-performance use cases like real-time chat applications or APIs for machine learning models. Figure 3: FastAPI vs Django: Async capabilities | by Nanda Gopal Pattanayak | Medium Automatic Interactive API Documentation Out of the box, FastAPI generates Swagger UI and ReDoc documentation for all API endpoints.

Python 153

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Flipboard

APRIL 23, 2025

RAG workflow: Converting data to actionable knowledge RAG consists of two major steps: Ingestion Preprocessing unstructured data, which includes converting the data into text documents and splitting the documents into chunks. Document chunks are then encoded with an embedding model to convert them to document embeddings.

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Flipboard

SEPTEMBER 3, 2023

If modern artificial intelligence has a founding document, a sacred text, it is Google’s 2017 research paper “Attention Is All You Need.” This paper introduced a new deep learning architecture known as the transformer, which has gone on to revolutionize the field of AI over the past half-decade.

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NYU Center for Data Science

JANUARY 18, 2024

Micah Goldblum , a Postdoctoral Researcher at CDS, has created exactly that, in a recent survey intended to capture the multifaceted views of influential figures in deep learning. Goldblum’s work, the first in a planned series, aims to document diverse opinions in the field, particularly those not amplified by social media platforms.

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AWS Machine Learning Blog

AUGUST 9, 2024

Question and answering (Q&A) using documents is a commonly used application in various use cases like customer support chatbots, legal research assistants, and healthcare advisors. In this collaboration, the AWS GenAIIC team created a RAG-based solution for Deltek to enable Q&A on single and multiple government solicitation documents.

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AWS Machine Learning Blog

NOVEMBER 6, 2023

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from scanned documents. Queries is a feature that enables you to extract specific pieces of information from varying, complex documents using natural language. MICR line format).

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AWS Machine Learning Blog

APRIL 7, 2025

The following use cases are well-suited for prompt caching: Chat with document By caching the document as input context on the first request, each user query becomes more efficient, enabling simpler architectures that avoid heavier solutions like vector databases. Please follow these detailed instructions:" "nn1.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

In today’s rapidly evolving landscape of artificial intelligence, deep learning models have found themselves at the forefront of innovation, with applications spanning computer vision (CV), natural language processing (NLP), and recommendation systems. If not, refer to Using the SageMaker Python SDK before continuing.

Deep Learning 119

Deep Learning Deep Learning Natural Language Processing Python 119

Towards AI

JANUARY 11, 2024

Photo by AltumCode on Unsplash As a data scientist, I used to struggle with experiments involving the training and fine-tuning of large deep-learning models. In this article, we’ll explore how to track hyperparameters and performance scores of deep learning models using kedro-viz.

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AWS Machine Learning Blog

MARCH 21, 2025

Research papers and engineering documents often contain a wealth of information in the form of mathematical formulas, charts, and graphs. Navigating these unstructured documents to find relevant information can be a tedious and time-consuming task, especially when dealing with large volumes of data.

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Google Research AI blog

FEBRUARY 7, 2023

The explosion in deep learning a decade ago was catapulted in part by the convergence of new algorithms and architectures, a marked increase in data, and access to greater compute. BERT ) to a factorized dual-encoder , an important setting for the task of scoring the relevance of a [ query , document ] pair.

Deep Learning 118

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Dataconomy

MARCH 21, 2025

Approaches to NLP NLP can be broadly categorized into rule-based systems and machine learning systems. Rule-based systems utilize predefined linguistic rules to analyze text, while machine learning systems rely on data-driven approaches to train models. Gensim: Primarily used for topic modeling and document similarity analysis.

Natural Language Processing 103

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Mlearning.ai

AUGUST 13, 2023

Document Intelligence Series — Part-1: Table Detection with YOLOv8 Photo by Mr Cup / Fabien Barral on Unsplash Introduction When dealing with unstructured data, you frequently encounter a situation where you must seek a resolution to efficiently retrieve information from a table within any document. Perform OCR.

Deep Learning 98

Deep Learning Deep Learning Python Data Science 98

Analytics Vidhya

APRIL 30, 2024

This enigmatic model has been released without official documentation, leading to speculation about its origins and capabilities. This new artificial intelligence (AI) model has recently emerged and is causing quite a stir in the tech community.

Artificial Intelligence 327

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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. This was the world of Transformers before the “Attention is All You Need” paper unveiled its revolutionary spotlight – the attention mechanism.

Analytics 318

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Analytics Vidhya

MAY 8, 2024

These models can understand and generate human-like text, enabling applications like chatbots and document summarization. Introduction to Ludwig The development of Natural Language Machines (NLP) and Artificial Intelligence (AI) has significantly impacted the field.

Artificial Intelligence 318

Artificial Intelligence Artificial Intelligence Analytics Analytics 318

Analytics Vidhya

FEBRUARY 2, 2024

Unstructured data, including text documents and social media posts, exacerbates this challenge with its inherent lack of predefined structure, making extracting meaningful insights even […] The post Ways of Converting Textual Data into Structured Insights with LLMs appeared first on Analytics Vidhya.

Big Data 305

Big Data Big Data Analytics Analytics 305

Analytics Vidhya

SEPTEMBER 2, 2021

This article was published as a part of the Data Science Blogathon Overview Sentence classification is one of the simplest NLP tasks that have a wide range of applications including document classification, spam filtering, and sentiment analysis. A sentence is classified into a class in sentence classification.

Natural Language Processing 299

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AWS Machine Learning Blog

FEBRUARY 7, 2024

In the first post of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. The following diagram represents each stage in a mortgage document fraud detection pipeline.

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ML ML AWS Data Profiling 138

Data Science Dojo

MARCH 4, 2024

Emerging as a key player in deep learning (2010s) The decade was marked by focusing on deep learning and navigating the potential of AI. Introduction of cuDNN Library: In 2014, the company launched its cuDNN (CUDA Deep Neural Network) Library. It provided optimized codes for deep learning models.

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AWS Machine Learning Blog

OCTOBER 23, 2024

For instance, when developing a medical search engine, obtaining a large dataset of real user queries and relevant documents is often infeasible due to privacy concerns surrounding personal health information. These PDFs will serve as the source for generating document chunks.

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PyImageSearch

DECEMBER 23, 2024

Jump Right To The Downloads Section Introduction to Approximate Nearest Neighbor Search In high-dimensional data, finding the nearest neighbors efficiently is a crucial task for various applications, including recommendation systems, image retrieval, and machine learning. product specifications, movie metadata, documents, etc.)

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AWS Machine Learning Blog

JUNE 11, 2024

release , you can now launch Neuron DLAMIs (AWS Deep Learning AMIs) and Neuron DLCs (AWS Deep Learning Containers) with the latest released Neuron packages on the same day as the Neuron SDK release. AWS DLCs provide a set of Docker images that are pre-installed with deep learning frameworks.

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Dataconomy

APRIL 21, 2025

Current approaches Modern NLP has seen a notable shift toward deep learning techniques and the use of large datasets. Gensim: Focused on topic modeling to facilitate deep text analysis. NLP Architect by Intel: Designed for advanced deep learning applications in NLP.

Natural Language Processing 91

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Data Science Dojo

SEPTEMBER 25, 2024

Compliance and Rights Management AI automates regulatory document analysis, ensuring compliance with ever-evolving regulations. It monitors content portfolios for compliance with predefined rules and policies, automates documentation and reporting processes, and flags potential compliance violations or discrepancies.

AI 448

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DrivenData Labs

APRIL 10, 2024

The Challenge ¶ Motivation ¶ Much of the world's healthcare data is stored in free-text documents, usually clinical notes taken by doctors. In the inference phase each document is processed independently of the others. Gleb Sokolov is an experienced deep learning engineer with a strong background in computer vision.

Computer Science 264

Computer Science Computer Science Machine Learning Machine Learning 264

Data Science Blog

FEBRUARY 23, 2023

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves.

Supervised Learning 264

Supervised Learning Machine Learning Machine Learning Deep Learning 264

PyImageSearch

JANUARY 20, 2025

text documents, software executables, and scientific data). Course information: 86 total classes 115+ hours of on-demand code walkthrough videos Last updated: October 2024 4.84 (128 Ratings) 16,000+ Students Enrolled I strongly believe that if you had the right teacher you could master computer vision and deep learning.

Deep Learning 113

Deep Learning Deep Learning Algorithm Computer Science 113

Data Science Dojo

SEPTEMBER 18, 2023

The rise of Generative AI While generative AI has been around for several decades, it has only recently become a reality thanks to the development of deep learning techniques. These techniques allow AI systems to learn from large amounts of data and generate new content that is indistinguishable from human-created content.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

This significant improvement showcases how the fine-tuning process can equip these powerful multimodal AI systems with specialized skills for excelling at understanding and answering natural language questions about complex, document-based visual information. For a detailed walkthrough on fine-tuning the Meta Llama 3.2

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DrivenData Labs

MAY 12, 2025

competition, winning solutions used deep learning approaches from facial recognition tasks (particularly ArcFace and EfficientNet) to help the Bureau of Ocean and Energy Management and NOAA Fisheries monitor endangered populations of beluga whales by matching overhead photos with known individuals.

Algorithm 130

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Flipboard

JUNE 20, 2023

We present the results of recent performance and power draw experiments conducted by AWS that quantify the energy efficiency benefits you can expect when migrating your deep learning workloads from other inference- and training-optimized accelerated Amazon Elastic Compute Cloud (Amazon EC2) instances to AWS Inferentia and AWS Trainium.

AWS 123

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AWS Machine Learning Blog

DECEMBER 12, 2024

For the detailed list of pre-set values, refer to the SDK documentation. For a full list of the available configs, including compute and networking, refer to the SDK documentation. We encourage you to try out the ModelTrainer class by referring to the SDK documentation and sample notebooks on the GitHub repo.

ML 103

ML ML Python AWS 103

Flipboard

FEBRUARY 25, 2025

He became a regular at AI hackathons, including the one where he met Reyes, whod written his thesis on deep learning and worked on language models at Microsoft and Hugging Face. Similarly, if a project has code that lacks commentsembedded explanations documenting what the software is doing and how it does ita Droid can add them.

AI 126

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