深度学习综述

One of the core topics of artificial intelligence is neural networks and deep learning, which imitate the working principle of the human brain and use multi-level neural connections to mine valuable knowledge and rules from data. The research of neural networks started in the 1940s and went through several ups and downs and innovations. It now covers many types and fields, such as convolutional neural networks, recurrent neural networks, speech recognition, computer vision and natural language processing. Deep learning refers to using multi-layer neural networks to solve complex nonlinear problems. It relies on massive data and computing resources, as well as efficient training and optimization techniques. Deep learning has achieved amazing progress in recent years, but also faces some difficulties and challenges, such as model interpretability, generalization ability, security and reliability. Deep learning is still a vibrant and promising research field, which is expected to open up more opportunities and possibilities for human intelligence and life. This article will briefly introduce some types of neural network structures and some deep learning model structures.