Research on the Application of Deep Learning Algorithm in Big Data Image Classification

Deep learning is the key and difficult point in the current application research of big data image classification. Compared with the traditional shallow network model, the multi-layer network structure with deep learning algorithm as the core can correctly express complex functions, thus presenting stronger characteristics of learning and representation ability and improving the accuracy of image classification. However, based on the current state of big data image classification, Restricted Boltzmann Machine (RBM) was found. As the basic unit of deep learning algorithm, has problems such as high complexity and low likelihood of training data during training, which directly increases the training time of deep learning model. Therefore, on the basis of understanding the deep learning algorithm, this paper studies and analyzes the image classification method and proposes the image classification method of multi-layer RBM network. The final empirical results show that, compared with other image classification methods, the image classification technique based on deep learning algorithm improves the accuracy of practical operation, and shows strong robustness and generalization.