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Active Learning for Text Classification
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Active Learning for Text Classification Overview

What is Active Learning for Text Classification?

Active Learning for Text Classification trains a text classification model using a small corpus of training data and provides the most appropriate samples from a huge corpus of unlabeled data to be annotated in order to improve the model accuracy significantly. Using Active Learning this algorithm helps in identifying the most effective data sample to be tagged first thus reducing the time and effort to build a usable Machine learning model.

Active Learning for Text Classification Details
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Product Description
Active Learning for Text Classification trains a text classification model using a small corpus of training data and provides the most appropriate samples from a huge corpus of unlabeled data to be annotated in order to improve the model accuracy significantly. Using Active Learning this algorithm helps in identifying the most effective data sample to be tagged first thus reducing the time and effort to build a usable Machine learning model.

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Description

Mphasis Stelligent, with its website located at https://stelligent.com/, specializes in providing DevOps automation and continuous delivery solutions on the Amazon Web Services (AWS) cloud platform. As part of Mphasis, a larger IT services company, Stelligent focuses on helping clients automate and accelerate the development, testing, and deployment of applications within AWS environments. Their suite of services includes consulting, engineering, and automation expertise to implement secure and scalable CI/CD pipelines, facilitating a faster go-to-market strategy for enterprises across various sectors. Stelligent's approach integrates tightly with AWS technologies, offering tools and practices that enhance the cloud capabilities of their customers, ensuring efficient and innovative cloud-based solutions.

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