The Overview of machine learning Key Branch, and then provide the complete protection of the deep neural network. It covers important critical concepts, testing methods, applications, issues related to assessment level (regression and classification), unattended learning (reduction set and dimension), active learning and semitracking (pre-attachment method) cover, and intensive learning. The scope of in-depth neural network communication includes Retrieval Neural Networks (RNNs), and word embedding and related technologies. Discussion issues, the online platform of intelligent library technology and easy relational tools are still so obvious that computer origin is a challenge and is based on the natural visualization of Digital Library (DL) related applications and large data analysis. To search the online platform of intelligent library documents based on the digital library image, recommend designing an assortment that adds descriptions to main images. First, propose a machine learning technique visual description appropriate to the representation of that image. The image is divided into regions based on the type of a particular area and then pointers. Second, propose an image classification method for the freedom of interpretation spaces. This feature is obtained by combining selection and kernel-based method classification.