BPT Natural Language Processing and Understanding

Introducing BPT Natural Language Processing (NLP) services requires a variety of development environments. Below is a description of the configuration of the natural language logic we plan to introduce to the BPT Platform

MLlib (Machine Learning Library): It is the default machine learning library in Spark, providing a variety of machine learning algorithms and tools. It can perform tasks such as regression, classification, clustering, collaborative filtering, dimensionality reduction, and more. MLlib is implemented on top of RDD, which allows you to perform machine learning tasks on large amounts of data in Spark's distributed environment.

GraphX: It is a library for image analysis that provides various algorithms for image structured data. It can run graph algorithms such as shortest path, PageRank, and connectivity analysis

Spark SQL: It is a module for structured data processing, allowing the processing of data in a style similar to SQL queries. It provides a Data Frame API to manipulate data and execute SQL queries.

Streaming: It is a module for real-time data streaming processing that enables the real-time processing of data streams. It supports structural streaming and can process large amounts of real-time data.