Remove document-classification
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From Data Swamp to Data Lake: Data Classification

Perficient

This is the third blog in a series that explains how organizations can prevent their Data Lake from becoming a Data Swamp, with insights and strategy from Perficient’s Senior Data Strategist and Solutions Architect, Dr. Chuck Brooks. In this blog, we discuss the fourth capability: Implementing classification-based security in the Data Lake.

Data 111
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Response to Cancer Treatment

John Snow Labs

The ability to precisely comprehend the intricate details documented in clinical reports is essential for informing subsequent treatment decisions, adjusting therapeutic strategies, and ultimately improving patient outcomes. Step 1: Transforms raw texts to `document` document = DocumentAssembler().setInputCol("text").setOutputCol("document")

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Cost-effective document classification using the Amazon Titan Multimodal Embeddings Model

AWS Machine Learning - AI

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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Use Context-Aware Data Classification for a Robust Data Security Posture

Prisma Clud

DSPM-based data classification offers a granular view that helps define adequate policies for the type, context and sensitivity of the data. In this blog post, we’ll present a set of data classification categories that can help you extract context from your data for richer and more accurate labeling. What Is Data Classification?

Data 52
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10 most in-demand generative AI skills

CIO

These skills include expertise in areas such as text preprocessing, tokenization, topic modeling, stop word removal, text classification, keyword extraction, speech tagging, sentiment analysis, text generation, emotion analysis, language modeling, and much more.

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New Applied ML Research: Few-shot Text Classification

Cloudera

Text classification is a ubiquitous capability with a wealth of use cases. While dozens of techniques now exist for the fundamental task of text classification, many of them require massive amounts of labeled data in order to prove useful. This is all well and good for words, but what about documents? the,” “at,” or “it”).

Research 104
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How to Extract Structured Data from Unstructured Text using LLMs

Xebia

But note that for very structured outputs, a simple classification model could also be trained once enough samples are collected. To read more about enforcing an LLM to give structured outputs, check out our previous blog post. It allows us to complete the task without training a model. In some cases however, pdfs span dozens of pages.