Batch Normalization
Batch Normalization ni mbinu ya mafunzo iliyoanzishwa na Sergey Ioffe na Christian Szegedy mwaka 2015 ambayo hurekebisha matokeo ya kabla ya uanzishaji wa kila safu kwa kutumia wastani na utofauti uliohesabiwa kutoka kwa kundi dogo (mini-batch) la sasa. Kwa kutuliza usambazaji wa pembejeo kwa kila safu wakati wa mafunzo, hupunguza kwa kiasi kikubwa mabadiliko ya ndani ya kiwambaza (internal covariate shift), ikiruhusu matumizi ya viwango vikubwa vya kujifunza na kufanya mitandao mirefu kufunzwa kwa kasi na kwa uaminifu zaidi.
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Vyanzo
- Ioffe, S. & Szegedy, C. (2015). Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. Proceedings of the 32nd International Conference on Machine Learning (ICML), PMLR 37, 448–456. link ↗
- Goodfellow, I., Bengio, Y. & Courville, A. (2016). Deep Learning (Ch. 8). MIT Press. ISBN: 978-0-262-03561-3
- Ioffe, S. & Szegedy, C. (2015). Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. arXiv preprint arXiv:1502.03167. link ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Batch Normalization (Normalizing Layer Activations per Mini-Batch). ScholarGate. https://scholargate.app/sw/deep-learning/batch-normalization
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