Optimizing Java Practical Techniques for Improved 完整版，不是early release

机器学习和数据挖掘方面的两本 世界名著 之一 本书从应用出发，原理非常完整。

Compilers Principles Techniques and Tools 2nd Edition 带完整目录

数学专业，研究生攻读代数方向的同学的基础课程，需要考博的同学也会需要

Nanotechnology has great potential in manufacturing, manipulating, observing, and functioning of materials, and understanding the physics and chemistry at the nanoscale, but it is limited to surface science and technology in two dimensions, with use of, for example, e-beam, ion beam, light beam, and atomic force through the processes of illumination, deposition, etching, andmodification of the surface. Available nanotechnological devices such as nanoelectronic circuits, high-density data storage, liquid-crystal displays, and micro and nanoelectromechanical systems (MEMSs and NEMSs) are all basically of two dimensions. However, future nanotechnology, in particular nanomanufacturing, should be made in three dimensions similar to the existing ordinary machinery. In the book Engines of Creation: The Coming Era of Nanotechnology (Doubleday, 1986), the author Eric Drexler discusses future nanotechnologies such as molecular assemblers, atom-by-atom building, and self-replicating machines. In the novel Prey (Harper Collins, 2002), Michael Crichton describes a machine that makes nanobots from bacteria, which turn into a nano-swarm attacking humans. The nanomachines appearing in those books are all three-dimensional machines.

"Algorithms: Design Techniques and Analysis" M H Alsuwaiyel 2016 | ISBN-10: 9814723649 | 572 pages 算法设计技巧与分析[2016] 英文版 Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) the solution to the formulated problem. One can solve a problem on its own using ad hoc techniques or by following techniques that have produced efficient solutions to similar problems. This requires the understanding of various algorithm design techniques, how and when to use them to formulate solutions, and the context appropriate for each of them.Algorithms: Design Techniques and Analysis advocates the study of algorithm design by presenting the most useful techniques and illustrating them with numerous examples — emphasizing on design techniques in problem solving rather than algorithms topics like searching and sorting. Algorithmic analysis in connection with example algorithms are explored in detail. Each technique or strategy is covered in its own chapter through numerous examples of problems and their algorithms.Readers will be equipped with problem solving tools needed in advanced courses or research in science and engineering.

网上的 Parsing Techniques 文档都没有书签，查找起来不方便，于是我为其添加了书签目录，方便查阅。

Modern Recording Techniques(9th) 英文无水印原版pdf 第9版 pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书

I.H.Written, E.Frank, M.Hall, C.J.Pal Highlights Explains how machine learning algorithms for data mining work. Helps you compare and evaluate the results of different techniques. Covers performance improvement techniques, including input preprocessing and combining output from different methods. Features in-depth information on probabilistic models and deep learning. Provides an introduction to the Weka machine learning workbench and links to algorithm implementations in the software.

* Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems 　　 * Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support 　　 * The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining 　　 * More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining 　　 * Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis