introduction to audio analysis: a matlab approach随书matlab代码。

刘桂荣的英文著作《Mesh Free Methods - Moving Beyond the Finite Element Method》pdf格式

the most classic book about machine learning and pattern recognition updated in 2015, presented in a more intuitive way. beginner 's guide!

机器人状态估计理论经典

State Estimation for Robotics A Matrix Lie Group Approach

飞行器动力学与控制经典英文著作

State Estimation for Robotics A Matrix Lie Group Approach

Flexures: Elements of Elastic Mechanisms 这本书提出了一些基本的弯曲几何和分析模型，可以评估为具体的设计应用。然后，作者超越这一基本解释，探索更复杂的问题。具体地，本文讨论了这些弯曲几何和分析模型的集成，以产生有用的机制，以精确的运动控制与快速的动态响应。这本书将是有用的高等本科和研究生，特别是那些希望获得能力在实验和机械科学。目前在相关领域工作的工程师和其他科学家也将受益于挠性。

美国州立大学电脑科学系必修课程之一。 非扫描版。带Index

Josh Patterson, Adam Gibson, "Deep Learning: A Practitioner's Approach" English | 2017 | ISBN: 1491914254 | Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J’s workflow tool Learn how to use DL4J natively on Spark and Hadoop