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How to classify comment text

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Now that youve created the app and trained a model to recognize comment spam, the next thing that youll need to do is to integrate the model into your iOS or Android app. So lets take a look at this process. In iOS, you use CocoaPods to specify external files to use. And these are specified in a Podfile, such as this one. And Google provide a pod for TensorFlow Lite called TensoFlowLiteSwift, that you can use to bring in the TensorFlow Lite libraries. These will give you an interface that allows you to use models directly in your iOS apps. For Android, Android Studio uses the Gradle build system, and this similarly lets you use external libraries in your app. So for this app, well use a library provided by Google called the TensorFlow Lite task library for text classification. And you include it like this. The TensorFlow Lite Task Libraries not only integrate the TensorFlow Lite runtime, similar to CocoaPods in iOS, but they also give you a set of high-level libraries that can h

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How do I classify text in NLP?

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.

How do you categorize comments?

The process of comment categorization gives the reviewer the opportunity to confirm, augment, refine, and apply comments to the most appropriate category(ies) and weight the comment by Priority (High, General, Low) and Type (Positive, Neutral, Negative).

What is an example of classifying text?

Some of the most well-known examples of text classification include sentiment analysis, topic labeling, language detection, and intent detection.

How do you classify text?

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.

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