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Neural Networks & Fuzzy Logic | Vinoth Kumar & R. Saravana Kumar | 1st Edition (2009) | S.K. Kataria & Sons (English Medium)
|
| 328-395 |
[Shipping Cost = Standard Mode, Expedite Mode]
Neural Networks & Fuzzy Logic | Vinoth Kumar & R. Saravana Kumar | 1st Edition (2009) | S.K. Kataria & Sons (English Medium)
Neural Networks & Fuzzy Logic is a comprehensive book written by Vinoth Kumar and R. Saravana Kumar. This 1st edition, published in 2009 by S.K. Kataria & Sons in English Medium, provides an in-depth understanding of two important topics in the field of artificial intelligence and machine learning. The book starts with an introduction to neural networks, explaining the basic concepts, architecture, and learning algorithms. It covers various types of neural networks such as feedforward neural networks, recurrent neural networks, and convolutional neural networks. The authors also delve into advanced topics like deep learning and its applications in computer vision, natural language processing, and speech recognition. Moving on to fuzzy logic, the book explains the principles of fuzzy sets and fuzzy logic systems. It discusses how fuzzy logic can be used to model uncertainty and imprecision in real-world problems. The authors provide examples of fuzzy logic applications in control systems, pattern recognition, and decision-making processes. Throughout the book, the authors use clear explanations and practical examples to help readers grasp complex concepts easily. They also include numerous illustrations, diagrams, and code snippets to enhance understanding. Additionally, each chapter ends with review questions and exercises to test the reader's comprehension. Whether you are a student studying artificial intelligence or a professional looking to expand your knowledge in neural networks and fuzzy logic, this book serves as a valuable resource. It bridges the gap between theory and practice by providing real-world examples and case studies that demonstrate the practical applications of these technologies. Overall, Neural Networks & Fuzzy Logic is a must-have for anyone interested in delving deeper into artificial intelligence and machine learning. With its comprehensive coverage of both topics and user-friendly approach to explaining complex concepts, this book is sure to become a go-to reference for students and professionals alike.
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Neural Networks & Fuzzy Logic is a comprehensive book written by Vinoth Kumar and R. Saravana Kumar. This 1st edition, published in 2009 by S.K. Kataria & Sons in English Medium, provides an in-depth understanding of two important topics in the field of artificial intelligence and machine learning. The book starts with an introduction to neural networks, explaining the basic concepts, architecture, and learning algorithms. It covers various types of neural networks such as feedforward neural networks, recurrent neural networks, and convolutional neural networks. The authors also delve into advanced topics like deep learning and its applications in computer vision, natural language processing, and speech recognition. Moving on to fuzzy logic, the book explains the principles of fuzzy sets and fuzzy logic systems. It discusses how fuzzy logic can be used to model uncertainty and imprecision in real-world problems. The authors provide examples of fuzzy logic applications in control systems, pattern recognition, and decision-making processes. Throughout the book, the authors use clear explanations and practical examples to help readers grasp complex concepts easily. They also include numerous illustrations, diagrams, and code snippets to enhance understanding. Additionally, each chapter ends with review questions and exercises to test the reader's comprehension. Whether you are a student studying artificial intelligence or a professional looking to expand your knowledge in neural networks and fuzzy logic, this book serves as a valuable resource. It bridges the gap between theory and practice by providing real-world examples and case studies that demonstrate the practical applications of these technologies. Overall, Neural Networks & Fuzzy Logic is a must-have for anyone interested in delving deeper into artificial intelligence and machine learning. With its comprehensive coverage of both topics and user-friendly approach to explaining complex concepts, this book is sure to become a go-to reference for students and professionals alike.
Search Keywords - Neural Networks, Fuzzy Logic, Artificial Intelligence Book, Machine Learning Textbook, Vinoth Kumar Books, R Saravana Kumar Publications, S.K Kataria & Sons Books, Neural Networks Basics, Fuzzy Logic Principles, Deep Learning Applications, Artificial Intelligence Algorithms, Computer Vision Concepts, Natural Language Processing Techniques, Speech Recognition Systems, Control Systems using Fuzzy Logic, . Pattern Recognition with Neural Networks, . Decision Making using Fuzzy Logic, . Artificial Intelligence Case Studies, . Best AI Books, . Top Machine Learning Textbooks
Product Details
| SKU / BOOK Code: | SKKS-NNFL-VKRSK-1E-2009-(E) |
| Publisher: | S.K. Kataria and Sons |
| Author: | Vinoth Kumar & R. Saravana Kumar |
| Binding Type: | Paperback |
| No. of Pages: | 300 |
| ISBN-10: | 9380027789 |
| ISBN-13: | 978-93-80027-78-4 |
| Edition: | 1st edition |
| Language: | English Medium |
| Publish Year: | 2009-01 |
| Weight (g): | 450 |
| 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
Neural Networks & Fuzzy Logic | Vinoth Kumar & R. Saravana Kumar | 1st Edition (2009) | S.K. Kataria & Sons (English Medium)
Neural Networks & Fuzzy Logic is a comprehensive book written by Vinoth Kumar and R. Saravana Kumar. This 1st edition, published in 2009 by S.K. Kataria & Sons in English Medium, provides an in-depth understanding of two important topics in the field of artificial intelligence and machine learning. The book starts with an introduction to neural networks, explaining the basic concepts, architecture, and learning algorithms. It covers various types of neural networks such as feedforward neural networks, recurrent neural networks, and convolutional neural networks. The authors also delve into advanced topics like deep learning and its applications in computer vision, natural language processing, and speech recognition. Moving on to fuzzy logic, the book explains the principles of fuzzy sets and fuzzy logic systems. It discusses how fuzzy logic can be used to model uncertainty and imprecision in real-world problems. The authors provide examples of fuzzy logic applications in control systems, pattern recognition, and decision-making processes. Throughout the book, the authors use clear explanations and practical examples to help readers grasp complex concepts easily. They also include numerous illustrations, diagrams, and code snippets to enhance understanding. Additionally, each chapter ends with review questions and exercises to test the reader's comprehension. Whether you are a student studying artificial intelligence or a professional looking to expand your knowledge in neural networks and fuzzy logic, this book serves as a valuable resource. It bridges the gap between theory and practice by providing real-world examples and case studies that demonstrate the practical applications of these technologies. Overall, Neural Networks & Fuzzy Logic is a must-have for anyone interested in delving deeper into artificial intelligence and machine learning. With its comprehensive coverage of both topics and user-friendly approach to explaining complex concepts, this book is sure to become a go-to reference for students and professionals alike.
Search Keywords - Neural Networks, Fuzzy Logic, Artificial Intelligence Book, Machine Learning Textbook, Vinoth Kumar Books, R Saravana Kumar Publications, S.K Kataria & Sons Books, Neural Networks Basics, Fuzzy Logic Principles, Deep Learning Applications, Artificial Intelligence Algorithms, Computer Vision Concepts, Natural Language Processing Techniques, Speech Recognition Systems, Control Systems using Fuzzy Logic, . Pattern Recognition with Neural Networks, . Decision Making using Fuzzy Logic, . Artificial Intelligence Case Studies, . Best AI Books, . Top Machine Learning Textbooks
Neural Networks & Fuzzy Logic is a comprehensive book written by Vinoth Kumar and R. Saravana Kumar. This 1st edition, published in 2009 by S.K. Kataria & Sons in English Medium, provides an in-depth understanding of two important topics in the field of artificial intelligence and machine learning. The book starts with an introduction to neural networks, explaining the basic concepts, architecture, and learning algorithms. It covers various types of neural networks such as feedforward neural networks, recurrent neural networks, and convolutional neural networks. The authors also delve into advanced topics like deep learning and its applications in computer vision, natural language processing, and speech recognition. Moving on to fuzzy logic, the book explains the principles of fuzzy sets and fuzzy logic systems. It discusses how fuzzy logic can be used to model uncertainty and imprecision in real-world problems. The authors provide examples of fuzzy logic applications in control systems, pattern recognition, and decision-making processes. Throughout the book, the authors use clear explanations and practical examples to help readers grasp complex concepts easily. They also include numerous illustrations, diagrams, and code snippets to enhance understanding. Additionally, each chapter ends with review questions and exercises to test the reader's comprehension. Whether you are a student studying artificial intelligence or a professional looking to expand your knowledge in neural networks and fuzzy logic, this book serves as a valuable resource. It bridges the gap between theory and practice by providing real-world examples and case studies that demonstrate the practical applications of these technologies. Overall, Neural Networks & Fuzzy Logic is a must-have for anyone interested in delving deeper into artificial intelligence and machine learning. With its comprehensive coverage of both topics and user-friendly approach to explaining complex concepts, this book is sure to become a go-to reference for students and professionals alike.
Search Keywords - Neural Networks, Fuzzy Logic, Artificial Intelligence Book, Machine Learning Textbook, Vinoth Kumar Books, R Saravana Kumar Publications, S.K Kataria & Sons Books, Neural Networks Basics, Fuzzy Logic Principles, Deep Learning Applications, Artificial Intelligence Algorithms, Computer Vision Concepts, Natural Language Processing Techniques, Speech Recognition Systems, Control Systems using Fuzzy Logic, . Pattern Recognition with Neural Networks, . Decision Making using Fuzzy Logic, . Artificial Intelligence Case Studies, . Best AI Books, . Top Machine Learning Textbooks
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