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Unleashing the Power of Applied Text Mining in Python: Revolutionize Your Data Analysis

Pickl AI

Introduction to Applied Text Mining in Python Before going ahead, it is important to understand, What is Text Mining in Python? Text mining is also known as text analytics or Natural Language Processing (NLP). What is text mining in NLP?

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NLP Landscape: Switzerland

NLP People

It’s Institute of Computational Linguistics , which includes the Phonetics Laboratory , lead by Martin Volk and Volker Dellwo, as well as the URPP Language and Space perform research in NLP topics, such as machine translation, sentiment analysis, speech recognition and dialect detection. University of St. Gallen The University of St.

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professionals

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ChatGPT: The Google Killer, Distributed Training with PyTorch and Azure ML, and Many Models Batch…

ODSC - Open Data Science

What to Expect in 2023: A Data Scientist’s Top 5 AI Predictions Between improved NLP and increased use of AI in finance, here are one data scientist’s 2023 AI predictions. Here’s how you can uncover actionable textual and geospatial patterns related to counter human trafficking using NLP.

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Leveraging user-generated social media content with text-mining examples

IBM Journey to AI blog

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Text analysis takes it a step farther by focusing on pattern identification across large datasets, producing more quantitative results.

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Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Pickl AI

5. Text Analytics and Natural Language Processing (NLP) Projects: These projects involve analyzing unstructured text data, such as customer reviews, social media posts, emails, and news articles. NLP techniques help extract insights, sentiment analysis, and topic modeling from text data.

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Data Demystified: What Exactly is Data?- 4 Types of Analytics

Pickl AI

Data Processing Data processing involves cleaning, transforming, and organizing the collected data to prepare it for analysis. This step is crucial for eliminating inconsistencies and ensuring data integrity. Data Analysis Data analysis is the heart of deriving insights from the gathered information.