Remove Categorization Remove Data Integration Remove Metadata Remove NLP
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Is There a Library for Cleaning Data before Tokenization? Meet the Unstructured Library for Seamless Pre-Tokenization Cleaning

Marktechpost

In Natural Language Processing (NLP) tasks, data cleaning is an essential step before tokenization, particularly when working with text data that contains unusual word separations such as underscores, slashes, or other symbols in place of spaces. The post Is There a Library for Cleaning Data before Tokenization?

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AI and Blockchain Integration for Preserving Privacy

Unite.AI

Blockchain technology can be categorized primarily on the basis of the level of accessibility and control they offer, with Public, Private, and Federated being the three main types of blockchain technologies.

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Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights

AWS Machine Learning Blog

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

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A brief history of Data Engineering: From IDS to Real-Time streaming

Artificial Corner

Data mining techniques include classification, regression, clustering, association rule learning, and anomaly detection. These techniques can be applied to a wide range of data types, including numerical data, categorical data, text data, and more. MapReduce: simplified data processing on large clusters.