Neural Networks And Machine Learning
Anu Sayal, Janhvi Jha, N Chaithra, Veethika Gupta, Ashulekha Gupta, Omdeep Gupta, Minakshi Memoria
Abstract
Recent years have seen an increase in the popularity of neural network (NN) research. The mammalian brain, which consists of billions of interconnected neurons, is renowned for its ability to perform computationally hard tasks, such as face recognition, body motion planning, and muscle activity control. In an effort to emulate the effectiveness of biological neural networks in learning, artificial neural networks (ANNs) were developed. The NN technique has been the topic of many studies over the last few decades, with applications in many fields including control engineering, automation, aerospace, psychology, economics, healthcare, and energy science. The objective of the discipline of machine learning is to create computers that can independently learn and improve. In this chapter, we have attempted to depict the types of neural networks and machine learning as well as their applications in different industrial disciplines such as science, commerce, and medicine.