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Introduction to Artificial Neural Network | Gunjan Goswami | 3rd Edition (2012) | S.K. Kataria & Sons | English Medium
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Introduction to Artificial Neural Network | Gunjan Goswami | 3rd Edition (2012) | S.K. Kataria & Sons | English Medium
The book "Introduction to Artificial Neural Network" by Gunjan Goswami is a comprehensive guide to understanding the fundamentals of artificial neural networks. This 3rd edition, published in 2012 by S.K. Kataria & Sons, provides a detailed overview of the key concepts and principles behind artificial neural networks, making it an essential resource for students, researchers, and professionals in the field of artificial intelligence. The book begins with an introduction to the basic concepts of neural networks, including neurons, synapses, and activation functions. It then covers topics such as feedforward and recurrent neural networks, backpropagation algorithm, and various types of neural network architectures. The author also discusses advanced topics such as deep learning, convolutional neural networks, and recurrent neural networks. One of the highlights of this book is its practical approach to learning artificial neural networks. The author provides numerous examples and case studies to help readers understand how neural networks can be applied in real-world scenarios. Additionally, the book includes exercises at the end of each chapter to test the reader's understanding of the material covered. Overall, "Introduction to Artificial Neural Network" is a valuable resource for anyone looking to gain a solid foundation in artificial neural networks. Whether you are a student studying machine learning or a professional working in the field of artificial intelligence, this book will provide you with the knowledge and skills needed to excel in this rapidly growing field.
Search Keywords - Introduction to Artificial Neural Network, Gunjan Goswami, 3rd Edition (2012), S.K. Kataria & Sons, Artificial Neural Networks basics, Feedforward Neural Networks, Backpropagation Algorithm, Deep Learning concepts, Convolutional Neural Networks, Recurrent Neural Networks, Neural Network Architectures, Machine Learning books, Artificial Intelligence resources, Best books on Neural Networks, Practical applications of Neural Networks, Understanding Activation Functions, Examples on Artificial Neural Networks, Case Studies on ANN, Neural Networks for beginners, Advanced topics in Artificial Intelligence
The book "Introduction to Artificial Neural Network" by Gunjan Goswami is a comprehensive guide to understanding the fundamentals of artificial neural networks. This 3rd edition, published in 2012 by S.K. Kataria & Sons, provides a detailed overview of the key concepts and principles behind artificial neural networks, making it an essential resource for students, researchers, and professionals in the field of artificial intelligence. The book begins with an introduction to the basic concepts of neural networks, including neurons, synapses, and activation functions. It then covers topics such as feedforward and recurrent neural networks, backpropagation algorithm, and various types of neural network architectures. The author also discusses advanced topics such as deep learning, convolutional neural networks, and recurrent neural networks. One of the highlights of this book is its practical approach to learning artificial neural networks. The author provides numerous examples and case studies to help readers understand how neural networks can be applied in real-world scenarios. Additionally, the book includes exercises at the end of each chapter to test the reader's understanding of the material covered. Overall, "Introduction to Artificial Neural Network" is a valuable resource for anyone looking to gain a solid foundation in artificial neural networks. Whether you are a student studying machine learning or a professional working in the field of artificial intelligence, this book will provide you with the knowledge and skills needed to excel in this rapidly growing field.
Search Keywords - Introduction to Artificial Neural Network, Gunjan Goswami, 3rd Edition (2012), S.K. Kataria & Sons, Artificial Neural Networks basics, Feedforward Neural Networks, Backpropagation Algorithm, Deep Learning concepts, Convolutional Neural Networks, Recurrent Neural Networks, Neural Network Architectures, Machine Learning books, Artificial Intelligence resources, Best books on Neural Networks, Practical applications of Neural Networks, Understanding Activation Functions, Examples on Artificial Neural Networks, Case Studies on ANN, Neural Networks for beginners, Advanced topics in Artificial Intelligence
Product Details
| SKU / BOOK Code: | SKKS-IANN-GG-3E2012-(E) |
| Publisher: | S.K. Kataria and Sons |
| Author: | Gunjan Goswami |
| Binding Type: | Paperback |
| No. of Pages: | 325 |
| ISBN-10: | 9350142961 |
| ISBN-13: | 9789350142967 |
| Edition: | 3rd edition |
| Language: | English Medium |
| Publish Year: | 2012-01 |
| Weight (g): | 550 |
| Product Condition: | New |
| Reading Age: | Above 10 Years |
| Country of Origin: | India |
| Genre: | Textbooks & Study Guides |
| Manufacturer: | S.K. Kataria and Sons |
| Importer: | S.K. Kataria and Sons |
| Packer: | Fullfilled by Supplier |
Product Description
Introduction to Artificial Neural Network | Gunjan Goswami | 3rd Edition (2012) | S.K. Kataria & Sons | English Medium
The book "Introduction to Artificial Neural Network" by Gunjan Goswami is a comprehensive guide to understanding the fundamentals of artificial neural networks. This 3rd edition, published in 2012 by S.K. Kataria & Sons, provides a detailed overview of the key concepts and principles behind artificial neural networks, making it an essential resource for students, researchers, and professionals in the field of artificial intelligence. The book begins with an introduction to the basic concepts of neural networks, including neurons, synapses, and activation functions. It then covers topics such as feedforward and recurrent neural networks, backpropagation algorithm, and various types of neural network architectures. The author also discusses advanced topics such as deep learning, convolutional neural networks, and recurrent neural networks. One of the highlights of this book is its practical approach to learning artificial neural networks. The author provides numerous examples and case studies to help readers understand how neural networks can be applied in real-world scenarios. Additionally, the book includes exercises at the end of each chapter to test the reader's understanding of the material covered. Overall, "Introduction to Artificial Neural Network" is a valuable resource for anyone looking to gain a solid foundation in artificial neural networks. Whether you are a student studying machine learning or a professional working in the field of artificial intelligence, this book will provide you with the knowledge and skills needed to excel in this rapidly growing field.
Search Keywords - Introduction to Artificial Neural Network, Gunjan Goswami, 3rd Edition (2012), S.K. Kataria & Sons, Artificial Neural Networks basics, Feedforward Neural Networks, Backpropagation Algorithm, Deep Learning concepts, Convolutional Neural Networks, Recurrent Neural Networks, Neural Network Architectures, Machine Learning books, Artificial Intelligence resources, Best books on Neural Networks, Practical applications of Neural Networks, Understanding Activation Functions, Examples on Artificial Neural Networks, Case Studies on ANN, Neural Networks for beginners, Advanced topics in Artificial Intelligence
The book "Introduction to Artificial Neural Network" by Gunjan Goswami is a comprehensive guide to understanding the fundamentals of artificial neural networks. This 3rd edition, published in 2012 by S.K. Kataria & Sons, provides a detailed overview of the key concepts and principles behind artificial neural networks, making it an essential resource for students, researchers, and professionals in the field of artificial intelligence. The book begins with an introduction to the basic concepts of neural networks, including neurons, synapses, and activation functions. It then covers topics such as feedforward and recurrent neural networks, backpropagation algorithm, and various types of neural network architectures. The author also discusses advanced topics such as deep learning, convolutional neural networks, and recurrent neural networks. One of the highlights of this book is its practical approach to learning artificial neural networks. The author provides numerous examples and case studies to help readers understand how neural networks can be applied in real-world scenarios. Additionally, the book includes exercises at the end of each chapter to test the reader's understanding of the material covered. Overall, "Introduction to Artificial Neural Network" is a valuable resource for anyone looking to gain a solid foundation in artificial neural networks. Whether you are a student studying machine learning or a professional working in the field of artificial intelligence, this book will provide you with the knowledge and skills needed to excel in this rapidly growing field.
Search Keywords - Introduction to Artificial Neural Network, Gunjan Goswami, 3rd Edition (2012), S.K. Kataria & Sons, Artificial Neural Networks basics, Feedforward Neural Networks, Backpropagation Algorithm, Deep Learning concepts, Convolutional Neural Networks, Recurrent Neural Networks, Neural Network Architectures, Machine Learning books, Artificial Intelligence resources, Best books on Neural Networks, Practical applications of Neural Networks, Understanding Activation Functions, Examples on Artificial Neural Networks, Case Studies on ANN, Neural Networks for beginners, Advanced topics in Artificial Intelligence
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