Classify radio text easily

Aug 6th, 2022
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How to quickly Classify radio text and improve your workflow

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How to classify radio text

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hi everyone my name is Michelle Sharfstein and today Im going to talk to you about fast text which is a library for text classification so in this tech talk Im gonna cover a few different things first why is text classification important and what are some applications of text classification then Im going to look at fast text the library itself and talk about how it builds classification models and then how it uses them and evaluates them and then Ill go through an example or two so that you can see it in practice so first why text classification there are actually a lot of applications of text classification that are incredibly relevant for us every single day so the first are around web application search and content ranking so if Im a user on on a website I want to find all of the texts that are related to sports its really important for every piece of text to be able to classified into its correct category so that when Im looking for sports all of the most relevant content c

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Some Examples of Text Classification: Sentiment Analysis. Language Detection. Fraud Profanity Online Abuse Detection.
Text Classification can be achieved through three main approaches: Rule-based approaches. These approaches make use of handcrafted linguistic rules to classify text. Machine learning approaches. We can use machine learning to train models on large sets of text data to predict categories of new text. Hybrid approaches.
Text Classification is the process of categorizing text into one or more different classes to organize, structure, and filter into any parameter. For example, text classification is used in legal documents, medical studies and files, or as simple as product reviews.
Text classification also known as text tagging or text categorization is the process of categorizing text into organized groups. By using Natural Language Processing (NLP), text classifiers can automatically analyze text and then assign a set of pre-defined tags or categories based on its content.
More formally, text classification is an analytical process that takes any text document as input and assigns a label (or classification) from a predetermined set of class labels.
Feature selection methods can be classified into 4 categories. Filter, Wrapper, Embedded, and Hybrid methods. Filter perform a statistical analysis over the feature space to select a discriminative subset of features.
More formally, text classification is an analytical process that takes any text document as input and assigns a label (or classification) from a predetermined set of class labels.

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