本书对所有重要的机器学习方法和新近研究趋势进行了深入探索，通过讲解监督学习的两大支柱 回归和分类，站在全景视角将这些繁杂的方法一一打通，形成了明晰的机器学习知识体系。 新版对内容做了全面更新，使各章内容相对独立。全书聚焦于数学理论背后的物理推理，关注贴近应用层的方法和算法，并辅以大量实例和习题，适合该领域的科研人员和工程师阅读，也适合学习模式识别、统计/自适应信号处理、统计/贝叶斯学习、稀疏建模和深度学习等课程的学生参考。 此外，本书的所有代码均可免费下载，包含MATLAB和Python两个版本。 第2版重要更新 重写了关于神经网络和深度学习的章节，以反映自第1版以来的新进展。这一章从感知器和前馈神经网络的基础概念开始讨论，对深度网络进行了深入研究，涵盖较新的优化算法、批标准化、正则化技术（如Dropout
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Product Details 基本信息 ISBN-13 书号 9781597492720 Author 作者 Theodoridis Pages Number 页数 984页 Publisher 出版社 Academic Press Publication Date 出版日期 20081001 Product Dimensions 商品尺寸 0 x 0 x 0 cm Shipping Weight 商品重量 2150 Book Description 内容简介 This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback. Thoroughly d
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模式识别- (希腊)Sergios Theodoridis(西格尔斯.西奥多里蒂斯), 电子工业出版社【正版现货】 正版图书，本店套装图书默认为单本，您下单前可咨询在线客服，谢谢！
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