Lecture
Support Vector Machine: Model Storage, Memory Usage, and Energy Consumption
Description
This lecture covers the storage requirements of a trained Support Vector Machine model, memory usage calculation for storing the model, training time complexity analysis, and energy consumption estimation for training the SVM. It delves into the impact of the number of support vectors, dimensions of the data, and training time on the overall model. Additionally, it explores the energy consumption comparison with a regular kettle, providing insights into the computational cost of SVM training.
Official source
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