Neural Networks for Beginners
Brian Murray
"Neural Networks for Beginners: An Easy-to-Follow Introduction to Artificial Intelligence and Deep Learning" is an essential guide to understanding the basics of neural networks, the fundamental technology behind artificial intelligence and deep...
Location:
United States
Description:
"Neural Networks for Beginners: An Easy-to-Follow Introduction to Artificial Intelligence and Deep Learning" is an essential guide to understanding the basics of neural networks, the fundamental technology behind artificial intelligence and deep learning. This book provides an in-depth exploration of neural network architectures and how they can be used to solve complex real-world problems in a variety of fields, including image and speech recognition, natural language processing, and time series analysis. Written for beginners, this book provides a clear and concise introduction to the concepts and techniques of neural networks, including the basics of machine learning and deep learning. It covers a range of topics, from the fundamentals of neural networks to building and training models using popular frameworks like TensorFlow and PyTorch, as well as advanced topics like transfer learning and reinforcement learning. With practical examples and clear explanations, "Neural Networks for Beginners" is a valuable resource for anyone looking to learn about this exciting field. Whether you are a student, a professional, or simply interested in the technology behind artificial intelligence, this book will help you understand the basics of neural networks and how they are used to solve real-world problems. Duration - 12h 5m. Author - Brian Murray. Narrator - Ray Collins. Published Date - Friday, 16 January 2026. Copyright - © 2025 Khin Soe ©.
Language:
English
Opening Credits
Duration:00:00:07
I Introduction
Duration:00:03:24
II Fundamentals of neural networks
Duration:00:13:42
III Building neural networks
Duration:00:44:22
IV Evaluating and improving neural networks
Duration:00:33:15
V Applications of neural networks
Duration:00:24:59
VI Advanced topics in neural networks
Duration:00:36:12
VII Ethics and future directions in neural networks
Duration:00:38:47
VIII Conclusion
Duration:00:12:24
Opening credits
Duration:00:00:13
II Understanding model evaluation
Duration:00:32:49
III Evaluating data warehouse models
Duration:00:39:29
IV Performance metrics for model evaluation
Duration:00:23:00
V Techniques for model evaluation
Duration:00:31:35
VI Data quality assessment
Duration:00:28:47
VII Model comparison and selection
Duration:00:16:01
VIII Challenges and best practices in
Duration:00:40:16
IX Future trends in model evaluation
Duration:00:28:32
X Conclusion
Duration:00:09:51
I Introduction to deep learning
Duration:00:34:32
II Getting started with deep learning
Duration:00:20:57
III Neural networks and layers
Duration:00:07:40
IV Data preparation and preprocessing
Duration:00:14:55
V Training deep neural networks
Duration:00:54:23
VI Deep learning frameworks
Duration:00:04:36
VII Deep learning applications
Duration:00:26:48
VIII Advanced deep learning techniques
Duration:00:07:26
IX Deploying deep learning models
Duration:00:27:39
X Case studies
Duration:00:37:03
XI Conclusion
Duration:00:25:28
Ending Credits
Duration:00:00:07