The invention discloses a deep learning human face identification method based on weighting L2 extraction. According to the method, firstly, the human face feature vector is extracted through various-convolution-kernel convolution, then, a weighting L2 extraction method is utilized for carrying out dimensionality reduction on the feature vector, and then, a local average normalizing processing method is adopted for normalizing the feature vector, so a layer of network in the deep learning is formed, the same method is used for building three layers of deep leaning networks, in addition, the three layers of deep learning networks are subjected to cascade connection for forming a layered three-layer deep learning network, and finally, a support vector machine classifier is utilized for carrying out human face training and identification. The deep learning human face identification method has the advantages that the weighting L2 extraction method is provided for realizing the feature dimensionality reduction, the over fitting problem in the training and the single feature problem in the traditional L2 extraction are solved, the feature vector dimensionality reduction is effectively realized, meanwhile, the human face identification performance can be improved, higher grade of features can be effectively extracted, the stability is high, and the identification performance is high.