Parallel Processing

Parallel processing is a computing technique in which multiple processors or cores work together to execute a single task or a group of related tasks simultaneously. This technique is used to speed up the processing of large amounts of data by dividing the workload into smaller, more manageable tasks that can be executed in parallel. Parallel processing can be achieved through various methods such as multi-threading, multi-processing, and distributed computing. In data science and artificial intelligence, parallel processing is used to train complex machine learning models, process large datasets, and perform simulations and calculations. Parallel processing can significantly reduce the time required to complete these tasks, making it an essential tool for data scientists and AI experts.
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