AWS Machine Learning Blog

APRIL 4, 2025

Overview: How Lumi uses machine learning for intelligent credit decisions As part of Lumis customer onboarding and loan application process, Lumi needed a robust solution for processing large volumes of business transaction data. They fine-tuned this model using their proprietary dataset and in-house data science expertise.

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AWS Machine Learning Blog

FEBRUARY 6, 2025

Scientists, epidemiologists, and biostatisticians implement a vast range of queries to capture complex, clinically relevant patient variables from real-world data. Expressing these variables as natural language queries allows users to express scientific intent and explore the full complexity of the patient timeline.

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AWS Machine Learning Blog

JANUARY 22, 2025

Users can review different types of events such as security, connectivity, system, and management, each categorized by specific criteria like threat protection, LAN monitoring, and firmware updates. About the Authors Asaf Fried leads the Data Science team in Cato Research Labs at Cato Networks. Member of Cato Ctrl.

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John Snow Labs

MAY 10, 2023

Despite the laborious nature of the task, the notes are not structured in a way that can be effectively analyzed by a computer. Structured data like CCDAs/FHIR APIs can help determine the disease but they give us a limited view of the actual patient record. This tool makes chart review of narrative text notes from EHRs easier.

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NVIDIA Developer

JUNE 2, 2021

Applications for natural language processing (NLP) have exploded in the past decade. With the proliferation of AI assistants and organizations infusing their businesses with more interactive human-machine experiences, understanding how NLP techniques can be used to manipulate, analyze, and generate text-based data is essential.

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ODSC - Open Data Science

APRIL 4, 2025

In the evolving field of natural language processing (NLP), data labeling remains a critical step in training machine learning models. While the demand for high-quality, labeled data continues to grow, the last two years have prompted (pun intended) a notable shift from manual annotation to automated methods.

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Pickl AI

MAY 23, 2023

Data Science is a growing field and more and more people are emerging to take up Data Science as their career choice. While Data Science courses can be considered beneficial for development of conceptual knowledge, Data Science competitions help in skill development.

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Marktechpost

SEPTEMBER 8, 2023

MonkeyLearn’s use of machine learning to streamline business processes and analyze text eliminates the need for countless man-hours of data entry. The ability to automatically pull data from incoming requests is a popular feature in MonkeyLearn. The users can construct data analysis and transformation procedures.

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Snorkel AI

JUNE 23, 2023

Labeled data remains biggest blocker More than a quarter of respondents said that the lack of high-quality labeled data presented the biggest blocker for enterprise AI projects. Labeling data” is when data scientists use an LLM to apply a categorical label to a document, such as categorizing an article as business or sports.

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Snorkel AI

JUNE 23, 2023

Labeled data remains biggest blocker More than a quarter of respondents said that the lack of high-quality labeled data presented the biggest blocker for enterprise AI projects. Labeling data” is when data scientists use an LLM to apply a categorical label to a document, such as categorizing an article as business or sports.

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ODSC - Open Data Science

APRIL 28, 2023

If a Natural Language Processing (NLP) system does not have that context, we’d expect it not to get the joke. Raw text is fed into the Language object, which produces a Doc object. cats” component of Docs, for which we’ll be training a text categorization model to classify sentiment as “positive” or “negative.”

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IBM Journey to AI blog

AUGUST 1, 2023

A foundation model is built on a neural network model architecture to process information much like the human brain does. They can also perform self-supervised learning to generalize and apply their knowledge to new tasks. Dev Developers can write, test and document faster using AI tools that generate custom snippets of code.

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IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data.

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AWS Machine Learning Blog

FEBRUARY 25, 2025

As AIDAs interactions with humans proliferated, a pressing need emerged to establish a coherent system for categorizing these diverse exchanges. The main reason for this categorization was to develop distinct pipelines that could more effectively address various types of requests.

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Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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Marktechpost

NOVEMBER 11, 2024

Seaborn simplifies the process of creating complex visualizations like heatmaps, scatter plots, and time series plots, making it a popular choice for exploratory data analysis and data storytelling. PyTorch is widely used in natural language processing, computer vision, and reinforcement learning.

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Pickl AI

JULY 10, 2023

What is R in Data Science? R is an open-source programming language that you can use for free and is compatible with different operating systems and platforms. As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. How is R Used in Data Science?

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Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. link] The process can be categorized into three agents: Execution Agent : The heart of the system, this agent leverages OpenAI’s API for task processing.

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Towards AI

AUGUST 25, 2023

In graduate school, a course in AI will usually have a quick review of the core ML concepts (covered in a previous course) and then cover searching algorithms, game theory, Bayesian Networks, Markov Decision Processes (MDP), reinforcement learning, and more. Speech and Language Processing. Be willing to share the entire dataset.

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Snorkel AI

JUNE 23, 2023

Labeled data remains biggest blocker More than a quarter of respondents said that the lack of high-quality labeled data presented the biggest blocker for enterprise AI projects. Labeling data” is when data scientists use an LLM to apply a categorical label to a document, such as categorizing an article as business or sports.

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Marktechpost

SEPTEMBER 20, 2024

Large language models (LLMs) have made significant leaps in natural language processing, demonstrating remarkable generalization capabilities across diverse tasks. This limitation poses a significant hurdle for AI-driven applications requiring structured LLM outputs integrated into their data streams.

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Topbots

JUNE 22, 2023

SA is a very widespread Natural Language Processing (NLP). So, to make a viable comparison, I had to: Categorize the dataset scores into Positive , Neutral , or Negative labels. Interestingly, ChatGPT tended to categorize most of these neutral sentences as positive. finance, entertainment, psychology).

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IBM Journey to AI blog

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language.

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Artificial Corner

JUNE 18, 2023

ChatGPT released by OpenAI is a versatile Natural Language Processing (NLP) system that comprehends the conversation context to provide relevant responses. Although little is known about construction of this model, it has become popular due to its quality in solving natural language tasks.

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Pickl AI

DECEMBER 26, 2024

Understanding Artificial Intelligence Artificial Intelligence refers to the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning, reasoning, problem-solving, perception, and language understanding.

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IBM Journey to AI blog

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

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ODSC - Open Data Science

MAY 24, 2023

To save time for our financial advisors, our team decided to experiment with generative natural language processing (NLP) models to assist them in their daily conversations with clients. About the authors: Clara Higuera Cabañes, PhD is a senior data scientist at BBVA AI Factory.

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Marktechpost

JULY 17, 2023

A few automated and enhanced features for feature engineering, model selection and parameter tuning, natural language processing, and semantic analysis are noteworthy. The platform makes collaborative data science better for corporate users and simplifies predictive analytics for professional data scientists.

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Flipboard

DECEMBER 6, 2023

Tools like LangChain , combined with a large language model (LLM) powered by Amazon Bedrock or Amazon SageMaker JumpStart , simplify the implementation process. Types of summarizations There are several techniques to summarize text, which are broadly categorized into two main approaches: extractive and abstractive summarization.

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Towards AI

FEBRUARY 20, 2024

If you want an overview of the Machine Learning Process, it can be categorized into 3 wide buckets: Collection of Data: Collection of Relevant data is key for building a Machine learning model. It isn't easy to collect a good amount of quality data. How Machine Learning Works?

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AWS Machine Learning Blog

JANUARY 30, 2023

Problem statement Machine learning has become an essential tool for extracting insights from large amounts of data. From image and speech recognition to natural language processing and predictive analytics, ML models have been applied to a wide range of problems. The data statistics are shown in the table.

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Marktechpost

NOVEMBER 1, 2024

Databricks Unified Data Analytics Platform Databricks provides a single cloud-based platform for the large-scale deployment of enterprise-grade AI and data analytics solutions. It is frequently used to spur creativity and quicken the creation of data-driven applications in a variety of industries, including technology and finance.

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Flipboard

OCTOBER 25, 2023

Why it’s challenging to process and manage unstructured data Unstructured data makes up a large proportion of the data in the enterprise that can’t be stored in a traditional relational database management systems (RDBMS). AWS AI services are designed to extract metadata from different types of unstructured data.

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ODSC - Open Data Science

SEPTEMBER 12, 2024

Now that artificial intelligence has become more widely accepted, some daring companies are looking at natural language processing (NLP) technology as the solution. This streamlines pulling data and referencing documents. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

An intelligent document processing (IDP) project usually combines optical character recognition (OCR) and natural language processing (NLP) to read and understand a document and extract specific terms or words. His focus is natural language processing and computer vision.

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Becoming Human

MAY 9, 2024

In this article, we’ll talk about what named entity recognition is and why it holds such an integral position in the world of natural language processing. Introduction about NER Named entity recognition (NER) is a fundamental aspect of natural language processing (NLP).

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Marktechpost

JULY 23, 2023

Turi Create To add suggestions, object identification, picture classification, image similarity, or activity categorization to your app, you can be an expert in machine learning. It includes built-in streaming graphics to analyze your data and focuses on tasks rather than algorithms.

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