John Snow Labs

NOVEMBER 5, 2024

This blog post explores how John Snow Labs’ Healthcare NLP & LLM library is transforming clinical trials by using advanced NER models to efficiently filter through large datasets of patient records. link] John Snow Labs’ Healthcare NLP & LLM library offers a powerful solution to streamline this process.

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John Snow Labs

JANUARY 30, 2025

This blog post explores how John Snow Labs Healthcare NLP & LLM library revolutionizes oncology case analysis by extracting actionable insights from clinical text. These approaches streamline oncology data analysis, enhance decision-making, and improve patient outcomes.

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AWS Machine Learning Blog

JUNE 25, 2024

Manually analyzing and categorizing large volumes of unstructured data, such as reviews, comments, and emails, is a time-consuming process prone to inconsistencies and subjectivity. By using the pre-trained knowledge of LLMs, zero-shot and few-shot approaches enable models to perform NLP with minimal or no labeled data.

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Marktechpost

MAY 7, 2024

Both the Natural Language Processing (NLP) and database communities are exploring the potential of LLMs in tackling the Natural Language to SQL NL2SQL task, which involves converting natural language queries into executable SQL statements consistent with user intent.

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John Snow Labs

JUNE 26, 2024

This blog post explores how John Snow Labs’ Healthcare NLP models are revolutionizing the extraction of critical insights on opioid use disorder. Traditional data analysis methods often fall short due to the unstructured nature of most medical data, such as clinical notes, patient records, and research articles.

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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. Text analysis takes it a step farther by focusing on pattern identification across large datasets, producing more quantitative results. What is text mining? positive, negative or neutral).

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Unite.AI

AUGUST 27, 2024

Using Natural Language Processing (NLP) and the latest AI models, Perplexity AI moves beyond keyword matching to understand the meaning behind questions. It allows you to save, annotate, and categorize resources, turning Perplexity into a personal knowledge base. It's like talking to a knowledgeable assistant.

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Marktechpost

DECEMBER 25, 2023

This tool enhances data exploration by integrating cutting-edge Natural Language Processing (NLP) techniques. VectorLink introduces a novel approach to handling data by allowing developers to create custom text embeddings for their information using cloud models.

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Pickl AI

DECEMBER 26, 2024

This synergy enhances Data Analysis, accelerates problem-solving, and opens new avenues in fields such as drug discovery, financial modeling, and climate science, promising significant advancements in various industries. These processes include learning, reasoning, problem-solving, perception, and language understanding.

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AssemblyAI

MAY 14, 2024

Automated Data Analysis Marvin integrates advanced AI models to provide automated transcription services that convert audio and video data into accurate, actionable text. It lets users analyze text to detect patterns, extract meaningful information, and even redact sensitive data (automatically). For example, Corti.ai

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Marktechpost

SEPTEMBER 8, 2023

Microsoft Power BI Microsoft Power BI, a powerful business intelligence platform that lets users filter through data and visualize it for insights, is another top AI tool for data analysis. Users may import data from practically anywhere into the platform and immediately create reports and dashboards.

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AssemblyAI

JANUARY 23, 2024

  By leveraging Deep Learning architectures and training on vast amounts of data, LLMs can process and understand more nuance and context in human language than traditional Natural Language Processing (NLP) models. 

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Towards AI

FEBRUARY 3, 2024

NLP Project: Speech recognition, chatbots, …. As a data scientist, we will explore the entire data set to understand each characteristic and identify any patterns existing if any in it. This process is called Exploratory Data Analysis(EDA). Let’s look at a few of them, for example.

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Pickl AI

AUGUST 1, 2023

Text mining is also known as text analytics or Natural Language Processing (NLP). It is the process of deriving valuable patterns, trends, and insights from unstructured textual data. Topic Modeling With text mining, it is possible to identify and categorize topics and themes within large collections of documents.

Data Analysis 52

Data Analysis Python Categorization Data Mining 52

ODSC - Open Data Science

FEBRUARY 6, 2023

Monitoring and Compliance Nonprofits can use benchmarking and data science to measure their operations’ effectiveness precisely and customize their workflows for improved outcomes. Real-time tracking during emergencies and optimizing rescue efforts can benefit greatly from data analysis and visualization.

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ODSC - Open Data Science

MARCH 13, 2023

As you know, ODSC East brings together some of the best and brightest minds in data science and AI. They are experts in machine learning, NLP, deep learning, data engineering, MLOps, and data visualization. Leonardo De Marchi also provides consultancy and training in NLP for small and large companies.

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John Snow Labs

APRIL 18, 2024

In this post, we explore the utilization of pre-trained models within the Healthcare NLP library by John Snow Labs to map medical terminology to the MedDRA ontology. Specifically, our aim is to facilitate standardized categorization for enhanced medical data analysis and interpretation.

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Marktechpost

NOVEMBER 27, 2024

Types of Machine Learning: Supervised Learning: Involves training a model on labeled data. Classification: Categorizing data into discrete classes (e.g., Unsupervised Learning: Involves training a model on unlabeled data. Clustering: Grouping similar data points together (e.g., spam filtering, sentiment analysis).

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Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Depending on the data they are provided, different classifiers may perform better or worse (eg. It is well understood that the more data a machine learning algorithm has, the more effective it may be. Uysal and Gunal, 2014).

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Viso.ai

OCTOBER 10, 2024

Pattern Recognition in Data Analysis What is Pattern Recognition? The identification of regularities in data can then be used to make predictions, categorize information, and improve decision-making processes. Explorative) The recognition problem is usually posed as either a classification or categorization task.

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Towards AI

AUGUST 16, 2023

Data description: This step includes the following tasks: describe the dataset, including the input features and target feature(s); include summary statistics of the data and counts of any discrete or categorical features, including the target feature.

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John Snow Labs

FEBRUARY 3, 2025

This post explores how John Snow Labs Healthcare NLP & LLM library can be used to extract genes and phenotypes from clinical text. By leveraging NLP techniques, we can transform unstructured medical data into actionable insights, enabling more efficient genetic research, clinical diagnostics, and personalized medicine.

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ODSC - Open Data Science

APRIL 10, 2023

Intermediate Machine Learning with scikit-learn: Pandas Interoperability, Categorical Data, Parameter Tuning, and Model Evaluation Thomas J. Fan | Staff Software Engineer | Quansight Labs In this session, you’ll learn about scikit-learn, a Python machine-learning library used by data science practitioners from many disciplines.

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Marktechpost

FEBRUARY 23, 2025

Advances in Natural Language Processing: Improvements in NLP have made it possible for AI agents to better understand and respond to human language, particularly useful in interactive applications. Resources from DigitalOcean and GitHub help us categorize these agents based on their capabilities and operational approaches.

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Heartbeat

MARCH 8, 2023

Source: Author Introduction Text classification, which involves categorizing text into specified groups based on its content, is an important natural language processing (NLP) task. It also provides a wide range of packages and features designed specifically for NLP and text classification.

Machine Learning 52

Machine Learning Algorithm Categorization NLP 52

John Snow Labs

SEPTEMBER 17, 2024

Let’s start with a brief introduction to Spark NLP and then discuss the details of the Stigmatization NER model with some concrete results. Healthcare NLP & LLM The Healthcare Library is a powerful component of John Snow Labs’ Spark NLP platform, designed to facilitate NLP tasks within the healthcare domain.

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Marktechpost

AUGUST 21, 2023

As a result, users can save time and effort in the data analysis process by eliminating the need for manual data preparation. With Luminal, users can easily apply AI-powered changes like summarization, auto-tagging, and auto-categorization on columns containing data of varying types, from language codes to company names.

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John Snow Labs

MAY 10, 2023

NLP is the technological innovator across every industry as it is shaping the future of humanity in various ways. With the support of NLP, doctors can be better equipped to make better diagnoses and analyze patients’ conditions. Significance of NLP in Healthcare Let’s discuss some uses of NLP in Healthcare.

Natural Language Processing 52

Natural Language Processing NLP Categorization Data Scientist 52

John Snow Labs

JANUARY 9, 2025

John Snow Labs Vs AWS Medical Comprehend Accuracy: Clinical NER We managed to find 6 common entity types returned by AWS and mapped with the entities in Healthcare NLP using ner_jsl and ner_clinical_large models: Test, Treatment, Medication, Anatomy, Condition, Procedure. The largest difference is observed in Anatomy entities by 24%.

NLP 52

NLP Large Language Models Data Analysis Categorization 52

Heartbeat

FEBRUARY 8, 2023

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

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AWS Machine Learning Blog

JUNE 7, 2023

title.text table_title 'The following table summarizes, by major security type, our cash, cash equivalents, restricted cash, and marketable securities that are measured at fair value on a recurring basis and are categorized using the fair value hierarchy (in millions):' Similarly, we can use the following code to extract the footers of the table.

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ODSC - Open Data Science

AUGUST 8, 2023

Sessions include, but are not limited to Introduction to Statistics for Data Science An Introduction to Data Wrangling with SQL Introduction to Python for Data Analysis Introduction to Machine Learning Days 2, 3, and 4 will feature sessions for data scientists of all levels from beginner to advanced.

Data Science 52

Data Science Deep Learning Machine Learning Python 52

Artificial Corner

AUGUST 29, 2023

This time, I embarked on a Data Science journey with British Airways (BA). As a data scientist at BA, our job will be to apply our data analysis and machine learning skills to derive insights that help BA drive revenue upwards. They are a flag carrier airline of the UK. The new distribution will be equal as such.

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AWS Machine Learning Blog

APRIL 17, 2023

For the purpose of this exercise, we use the Titanic dataset , a popular dataset in the ML community, which has now been added as a sample dataset within Data Wrangler. Solution overview Data Wrangler provides over 40 built-in connectors for importing data. One-hot encoding Values in the Embarked columns are categorical values.

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Pickl AI

JULY 10, 2023

As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. The programming language can handle Big Data and perform effective data analysis and statistical modelling. R’s workflow support enhances productivity and collaboration among data scientists.

Data Science 52

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Viso.ai

DECEMBER 20, 2023

However, unsupervised learning has its own advantages, such as being more resistant to overfitting (the big challenge of Convolutional Neural Networks ) and better able to learn from complex big data, such as customer data or behavioral data without an inherent structure.

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AWS Machine Learning Blog

APRIL 12, 2023

Our ML models include emotion detection, transcription, and NLP-powered conversational analysis that categorizes violations and provides a rank score to determine how confident it is that a violation has occurred. Violations are flagged to human moderators who can take action against bad actors.

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