Understanding the Evolution of Neural Networks

Author(s)	Mr. Saurabh Sankhla, Mr. Lokesh Yadav, Dr. Priyanka Makkar, Dr. Anil Mishra
Country	India
Abstract	Neural networks are computer algorithms that attempt to model itself after the human brain. The networks have over the years evolved into very simple systems to very strong models that are capable of recognizing faces, translating languages as well as driving cars even developing an image. This has evolved due to improved algorithms, increased data as well as powerful computers. The paper covers the beginning of neural networks, the way they evolved gradually, and the significance of every step. It discusses the earlier models, including perceptron, multilayer networks, deep learning, convolutional networks, recurrent networks, transformers and current AI models. It is intended to provide a basic conception of the way neural networks evolved over the years and how they became smarter and more effective as a result of these changes.
Keywords	Engineering Neural Networks, Evolution, Perceptron, Deep Learning, Artificial Neurons, Machine Learning, CNNs, RNNs, Transformers, AI Models
Field	Computer Applications
Published In	Volume 7, Issue 6, November-December 2025
Published On	2025-12-07
DOI	https://doi.org/10.36948/ijfmr.2025.v07i06.62580

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research