AI News, Automated Text Classification Using Machine Learning

Automated Text Classification Using Machine Learning

Digitization has changed the way we process and analyze information.

From web pages to emails, science journals, e-books, learning content, news and social media are all full of textual data.

And, using machine learning to automate these tasks, just makes the whole process super-fast and efficient.

As Jeff Bezos said in his annual shareholder’s letter, Over the past decades, computers have broadly automated tasks that programmers could describe with clear rules and algorithms.

In this post, we talk about the technology, applications, customization, and segmentation related to our automated text classification API.

During the testing phase, the algorithm is fed with unobserved data and classifies them into categories based on the training phase.

It can operate for special use cases such as identifying emergency situation by analyzing millions of online information.

To identify emergency situation among millions of online conversation, the classifier has to be trained with high accuracy.

It needs special loss functions, sampling at training time and methods like building a stack of multiple classifiers each refining the results of previous one to solve this problem.

The algorithms are given a set of tagged/categorized text (also called train set) based on which they generate AI models, these models when further given the new untagged text, can automatically classify them.

The image below shows the nearest neighbors of the tweet “reliance jio prime membership at rs 99 : here’s how to get rs 100 cashback…”.

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