Neural networks and deep learning technologies underpin most of the advanced intelligent applications today. In this article, Dr. Sun Fei (Danfeng), a high-level algorithms expert from Alibaba's Search Department, will provide a brief overview of the evolution of neural networks and discuss the latest approaches in the field. The article is primarily centered on the following five items:
- The Evolution of Neural Networks
- Sensor Models
- Feed-forward Neural Networks
- Back-propagation
- Deep Learning Basics
1. The Evolution of Neural Networks
Before we dive into the historical development of neural networks, let's first introduce the concept of a neural network. A neural network is primarily a computing model that simulates the workings of the human brain at a simplified level. This type of model uses a large number of computational neurons which connect via layers of weighted connections. Each layer of neurons is capable of performing large-scale parallel computing and passing information between them.
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