{"product_id":"9783032147455","title":"Practical Neural Networks in Python and MATLAB","description":"\u003ch1\u003ePractical Neural Networks in Python and MATLAB\u003c\/h1\u003e \u003ch2\u003eZhang, Chunwei; Li, Tianpeng; Dai, Ying; Sun, Li; Mohammadzadeh, Ardashir\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif;\"\u003eA Comprehensive Guide to Theory and Implementation.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif;\"\u003eBridging the gap between theory and practice with this extensive guide to neural networks, featuring parallel implementations in both Python and MATLAB.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif;\"\u003eNavigating the complex landscape of neural networks requires not only a firm grasp of theoretical foundations but also the practical skills to implement them effectively. \u003cem\u003ePractical Neural Networks in Python and MATLAB\u003c\/em\u003e is designed to be a definitive resource, offering a unique dual-language approach to mastering these powerful models.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif;\"\u003eKey Features:\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0in;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph; line-height: normal; mso-list: l1 level1 lfo1; tab-stops: list .5in;\"\u003e\n\u003cstrong\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003eA Dual-Language, Integrated Approach:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003e This book provides a side-by-side exploration of neural networks in both \u003cstrong\u003ePython\u003c\/strong\u003e and \u003cstrong\u003eMATLAB\u003c\/strong\u003e. This methodology allows you to leverage Python's rich deep learning ecosystem (TensorFlow, Keras, PyTorch) and MATLAB's specialized toolboxes, giving you the flexibility to work within your preferred environment or across different project requirements.\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph; line-height: normal; mso-list: l1 level1 lfo1; tab-stops: list .5in;\"\u003e\n\u003cstrong\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003eComprehensive Coverage of Algorithms and Architectures:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003e Move beyond basic backpropagation. The text provides a systematic review of fundamental and advanced training algorithms, including Gradient Descent, Newton's Method, Levenberg-Marquardt, Recursive Least Squares (RLS), and metaheuristics like Genetic Algorithms and Particle Swarm Optimization. Furthermore, it offers a detailed survey of over 25 major neural network architectures, from foundational Perceptrons and Feedforward Networks to advanced systems like CNNs, RNNs (LSTM, GRU), Autoencoders, GANs, and Deep Belief Networks.\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph; line-height: normal; mso-list: l1 level1 lfo1; tab-stops: list .5in;\"\u003e\n\u003cstrong\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003ePractical, Code-Oriented Learning: \u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003eEach concept and architecture is accompanied by ready-to-run code examples. This practical focus ensures that you can immediately translate theoretical understanding into functional code, experiment with parameters, and adapt the implementations to your own unique challenges.\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph; line-height: normal; mso-list: l1 level1 lfo1; tab-stops: list .5in;\"\u003e\n\u003cstrong\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003eReal-World Application and Case Studies:\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003e The learning is grounded in practicality through diverse case studies across multiple domains. You will find applications in medical diagnostics (e.g., diabetes classification), time-series forecasting (e.g., air quality prediction), system identification, natural language processing, and more. These examples provide complete pipelines from data preprocessing and model training to evaluation and visualization.\u003c\/span\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif;\"\u003eThis Book is Ideal For:\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul style=\"margin-top: 0in;\" type=\"disc\"\u003e\n\u003cli class=\"MsoNormal\" style=\"margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph; line-height: normal; mso-list: l0 level1 lfo2; tab-stops: list .5in;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003eUniversity students and researchers in Computer Science, Artificial Intelligence, Engineering, and related fields.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph; line-height: normal; mso-list: l0 level1 lfo2; tab-stops: list .5in;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003eR\u0026amp;D engineers and scientists working in algorithm development, data analysis, and intelligent systems.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"MsoNormal\" style=\"margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph; line-height: normal; mso-list: l0 level1 lfo2; tab-stops: list .5in;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif;\"\u003eAny practitioner seeking a thorough, hands-on understanding of neural networks with the flexibility to work in both Python and MATLAB environments.\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp style=\"text-align: justify;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: DengXian; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;\"\u003eIn essence, \u003cem\u003ePractical Neural Networks in Python and MATLAB \u003c\/em\u003eserves as an invaluable companion for anyone looking to deepen their expertise in neural networks. It is more than a textbook; it is a practical toolkit designed to accelerate your research, enhance your projects, and provide a clear, comprehensive reference for the key architectures and algorithms shaping the field of AI today.\u003c\/span\u003e\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2026-04-24\u003c\/p\u003e \u003cp\u003eFormat: Hardcover\u003c\/p\u003e \u003cp\u003eISBN-13: 9783032147455\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-032-14746-2\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 167\u003c\/p\u003e ","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":44804281663628,"sku":"9783032147455","price":71.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783032147455.jpg?v=1779654432","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783032147455","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}