Dataconomy

APRIL 30, 2025

Embeddings in machine learning play a crucial role in transforming how machines interpret and understand complex data. This technology allows data to be represented in a way that captures its underlying structure, enabling algorithms to process it more effectively. What are embeddings in machine learning?

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AWS Machine Learning Blog

MAY 20, 2025

In the mortgage servicing industry, efficient document processing can mean the difference between business growth and missed opportunities. Onity processes millions of pages across hundreds of document types annually, including legal documents such as deeds of trust where critical information is often contained within dense text.

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Flipboard

APRIL 23, 2025

Traditional keyword-based search mechanisms are often insufficient for locating relevant documents efficiently, requiring extensive manual review to extract meaningful insights. This solution improves the findability and accessibility of archival records by automating metadata enrichment, document classification, and summarization.

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Dataconomy

MAY 4, 2023

Machine learning applications in healthcare are rapidly advancing, transforming the way medical professionals diagnose, treat, and prevent diseases. In this rapidly evolving field, machine learning is poised to drive significant advancements in healthcare, improving patient outcomes and enhancing the overall healthcare experience.

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Dataconomy

APRIL 16, 2025

Clustering in machine learning is a fascinating method that groups similar data points together. What is clustering in machine learning? Clustering is a subset of unsupervised learning where the goal is to categorize a set of objects into groups based on their similarities.

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Clustering Machine Learning Machine Learning Supervised Learning 91

AWS Machine Learning Blog

MAY 15, 2025

The banking industry has long struggled with the inefficiencies associated with repetitive processes such as information extraction, document review, and auditing. By using cutting-edge generative AI and deep learning technologies, Apoidea has developed innovative AI-powered solutions that address the unique needs of multinational banks.

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Dataconomy

APRIL 30, 2025

Intelligent document processing (IDP) is transforming the way businesses manage their documentation and data management processes. By harnessing the power of emerging technologies, organizations can automate the extraction and handling of data from various document types, significantly enhancing operational workflows.

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How to Learn Machine Learning

DECEMBER 24, 2024

If you’re diving into the world of machine learning, AWS Machine Learning provides a robust and accessible platform to turn your data science dreams into reality. Introduction Machine learning can seem overwhelming at first – from choosing the right algorithms to setting up infrastructure.

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Dataconomy

APRIL 30, 2025

Datasets in Machine Learning play a pivotal role in the development of intelligent systems. Without high-quality datasets, machine learning models struggle to achieve accuracy and reliability. What are datasets in machine learning? They can vary widely in size, complexity, and types of data contained.

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Flipboard

MARCH 11, 2025

For years, businesses, governments, and researchers have struggled with a persistent problem: How to extract usable data from Portable Document Format (PDF) files. Read full article Comments

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Flipboard

DECEMBER 3, 2024

As a global leader in agriculture, Syngenta has led the charge in using data science and machine learning (ML) to elevate customer experiences with an unwavering commitment to innovation. Efficient metadata storage with Amazon DynamoDB – To support quick and efficient data retrieval, document metadata is stored in Amazon DynamoDB.

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Towards AI

JULY 15, 2024

R has become ideal for GIS, especially for GIS machine learning as it has topnotch libraries that can perform geospatial computation. R has simplified the most complex task of geospatial machine learning and data science. Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI.

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Dataconomy

AUGUST 31, 2023

Classification in machine learning involves the intriguing process of assigning labels to new data based on patterns learned from training examples. Machine learning models have already started to take up a lot of space in our lives, even if we are not consciously aware of it. 0 or 1, yes or no, etc.).

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Data Science Dojo

MARCH 2, 2024

However, there are more options and opportunities thanks to technological development, including AI algorithms and field boundary detection with satellite technologies. In this piece, we will delve into technologies driving the field, such as remote sensing and cutting-edge algorithms.

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How to Learn Machine Learning

MAY 2, 2025

Welcome to this comprehensive guide on Azure Machine Learning , Microsoft’s powerful cloud-based platform that’s revolutionizing how organizations build, deploy, and manage machine learning models. This is where Azure Machine Learning shines by democratizing access to advanced AI capabilities.

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Data Science Dojo

SEPTEMBER 7, 2023

Just like people, Algorithmic biases can occur sometimes. AI algorithms are used to make decisions about everything from who gets a loan to what ads we see online. However, AI algorithms can be biased, which can have a negative impact on people’s lives. Thinking why? Well, think of AI as making those characters.

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AWS Machine Learning Blog

OCTOBER 10, 2024

Amazon Lookout for Vision , the AWS service designed to create customized artificial intelligence and machine learning (AI/ML) computer vision models for automated quality inspection, will be discontinuing on October 31, 2025.

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AWS Machine Learning Blog

APRIL 11, 2024

Organizations across industries want to categorize and extract insights from high volumes of documents of different formats. Manually processing these documents to classify and extract information remains expensive, error prone, and difficult to scale. Categorizing documents is an important first step in IDP systems.

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Database AWS Algorithm ML 137

Towards AI

JULY 23, 2024

Let us delve into machine learning-powered change detection, where innovative algorithms and spatial analysis combine to completely revolutionize how we see and react to our ever-changing surroundings. GEE offers strong tools for handling and examining big geographic datasets and change detection for machine learning.

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Flipboard

JANUARY 24, 2025

Overview of vector search and the OpenSearch Vector Engine Vector search is a technique that improves search quality by enabling similarity matching on content that has been encoded by machine learning (ML) models into vectors (numerical encodings). To learn more, refer to the documentation.

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Flipboard

DECEMBER 6, 2023

The model then uses a clustering algorithm to group the sentences into clusters. Implementation includes the following steps: The first step is to break down the large document, such as a book, into smaller sections, or chunks. It works by first embedding the sentences in the text using BERT.

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Dataconomy

APRIL 17, 2025

Feature engineering is a vital aspect of machine learning that involves the creative and technical process of transforming data into a format that enhances model performance. The importance of feature engineering Feature engineering is crucial for improving the accuracy and reliability of machine learning models.

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Dataconomy

MARCH 21, 2025

This remarkable intersection of AI, machine learning, and linguistics is shaping the future of communication in profound ways. By enabling machines to understand complex linguistic structures, NLP helps bridge communication gaps and enhances user engagement. What is Natural Language Processing (NLP)?

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Dataconomy

FEBRUARY 6, 2024

One area where AI has made substantial strides is medical scribing, transforming the way healthcare professionals document patient encounters. In this article, we will delve into the best 5 medical AI scribes that have garnered attention for their contributions to streamlining medical documentation processes in healthcare.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles. As Principal grew, its internal support knowledge base considerably expanded.

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AWS Machine Learning Blog

NOVEMBER 25, 2024

You can try out the models with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. To learn more, refer to the API documentation. You can change these configurations by specifying non-default values in JumpStartModel.

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Dataconomy

MAY 22, 2023

But what exactly is distributed learning in machine learning? In this article, we will explore the concept of distributed learning and its significance in the realm of machine learning. Why is it so important? This process is often referred to as training or model optimization.

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Flipboard

DECEMBER 18, 2024

improves search results for best matching 25 (BM25), a keyword-based algorithm that performs lexical search, in addition to semantic search. Lexical search relies on exact keyword matching between the query and documents. For a natural language query searching for super hero toys, it retrieves documents containing those exact terms.

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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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IBM Journey to AI blog

MAY 20, 2024

Machine learning (ML) has become a critical component of many organizations’ digital transformation strategy. From predicting customer behavior to optimizing business processes, ML algorithms are increasingly being used to make decisions that impact business outcomes.

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Machine Learning Machine Learning Data Scientist ML 110

Dataconomy

APRIL 14, 2025

Reproducible AI is becoming a cornerstone of reliable machine learning practices. Reproducible AI refers to the capability to duplicate machine learning (ML) processes accurately, ensuring consistent outcomes as initially intended. Strategies to control or document random seeds can mitigate these effects.

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Data Science Dojo

AUGUST 24, 2023

MLOps emphasizes the need for continuous integration and continuous deployment (CI/CD) in the ML workflow, ensuring that models are updated in real-time to reflect changes in data or ML algorithms. Complexity and Diversity of ML Models : Evaluate the range of algorithms, model architectures, and technologies used in your organization.

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Data Science Dojo

JULY 2, 2023

By analyzing diverse data sources and incorporating advanced machine learning algorithms, LLMs enable more informed decision-making, minimizing potential risks. Entity recognition: It reduces human error by classifying documents and minimizing manual and repetitive work.

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DrivenData Labs

MAY 12, 2025

In the Pose Bowl competition, winning solutions explored ways to implement object detection algorithms on limited hardware for use in space. Example output from Zamba Cloud, an application developed for conservation researchers building on data and algorithms from the Pri-matrix Factorization challenge.

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Data Science Dojo

JUNE 10, 2024

Here are some key ways data scientists are leveraging AI tools and technologies: 6 Ways Data Scientists are Leveraging Large Language Models with Examples Advanced Machine Learning Algorithms: Data scientists are utilizing more advanced machine learning algorithms to derive valuable insights from complex and large datasets.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

Generation : Here are some potential long-term impacts of AI and blockchain on the global financial industry: Automation of routine tasks – AI and machine learning can automate many routine financial tasks like loan processing, fraud detection, client onboarding etc. This could improve outcomes and reduce waste in the system.

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Data Science Dojo

JANUARY 22, 2025

Heres how embeddings power these advanced systems: Semantic Understanding LLMs use embeddings to represent words, sentences, and entire documents in a way that captures their semantic meaning. The process enables the models to find the most relevant sections of a document or dataset, improving the accuracy and relevance of their outputs.

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