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Learning and classification of MNIST data sets based on BP neural network written by MATLAB
Update : 2025-04-20 Size : 1kb Publisher : filament

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Approximation of the same nonlinear system based on cerebellar model neural network and BP network
Update : 2025-04-20 Size : 25kb Publisher : 爱美菊菊

Wondering is enough: Uncertainty about category information undermines face recognition
Update : 2025-04-20 Size : 9kb Publisher : TRACE5

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Energy storage capacity optimization
Update : 2025-04-20 Size : 1kb Publisher : 小青年001

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Based on Python language, using tensorflow machine learning architecture, two-layer convolutional neural network, CiFar data set image classification function.
Update : 2019-06-04 Size : 2kb Publisher : 奋斗到天亮

Machine learning actual supporting code, very very good information, you can download the learning.
Update : 2025-04-20 Size : 37.48mb Publisher : NEURR

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MNIST data set is a handwritten data set, which consists of four parts: a training picture set, a training label set, a test picture set and a test label set. We can see that this data set is not a normal text file or pi
Update : 2025-04-20 Size : 37.16mb Publisher : 陈陈123456

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Machine Learning // Python / interview notes
Update : 2025-04-20 Size : 26kb Publisher : 李二小


Update : 2025-04-20 Size : 1.25mb Publisher : zuoren

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The deep neural network algorithm can be directly used for model training and machine learning. The algorithm is reliable.
Update : 2025-04-20 Size : 14.42mb Publisher : makun

multihead_joint_entity_relation_extraction pytorch torflow
Update : 2025-04-20 Size : 364kb Publisher : adasdaaaa

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Using convolution neural network to extract features and classify them
Update : 2025-04-20 Size : 21.32mb Publisher : @东方
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