Load Balancing
Load balancing is the process of distributing network traffic across multiple servers to ensure that no single server is overwhelmed with traffic, thereby improving the overall performance, availability, and reliability of the system. In the context of data science and artificial intelligence, load balancing is used to distribute computational tasks across multiple machines or nodes in a cluster, allowing for faster processing of large datasets and complex algorithms. Load balancing algorithms can be static or dynamic, and can take into account factors such as server capacity, network latency, and user demand to optimize the distribution of workloads. Load balancing is a critical component of many data science and AI applications, particularly those that involve real-time data processing, machine learning, and deep learning.
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