Congestion
In Data Science, congestion refers to the situation where the amount of data being transmitted through a network exceeds its capacity to handle it, resulting in a slowdown or complete halt of data transfer. Congestion can occur due to various reasons such as network overload, hardware failure, or software errors. Congestion can also occur in machine learning models when the amount of data being processed exceeds the capacity of the system, leading to slower processing times and reduced accuracy. Congestion can be managed through various techniques such as load balancing, traffic shaping, and congestion control algorithms.
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