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Engineering Mechanics Is A Core Subject Taught To Engineering Students In The First Year Of Their Course By Going Through This Subject. The Students Develop The Capability To Model Actual Problem In To An Engineering Problem And Find The Solutions Using Laws At Mechanics. The Neat Free-Body Diagrams Are Presented And Problems Are Solved Systematically To Make The Procedure Clear. Throughout Si Units And Standard Notations Are Recommended By Indian Standard Codes Are Used. The Author Has Tried To Meet The Needs Of Syllabi Of Almost All Universities.
Our understanding of the fundamental processes of the natural world is based to a large extent on partial differential equations (PDEs). The second edition of Partial Differential Equations provides an introduction to the basic properties of PDEs and the ideas and techniques that have proven useful in analyzing them. It provides the student a broad perspective on the subject, illustrates the incredibly rich variety of phenomena encompassed by it, and imparts a working knowledge of the most important techniques of analysis of the solutions of the equations. In this book mathematical jargon is minimized. Our focus is on the three most classical PDEs: the wave, heat and Laplace equations. Advanced concepts are introduced frequently but with the least possible technicalities. The book is flexibly designed for juniors, seniors or beginning graduate students in science, engineering or mathematics.
Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
The lecture notes presented here in facsimile were prepared by Enrico Fermi for students taking his course at the University of Chicago in 1954. They are vivid examples of his unique ability to lecture simply and clearly on the most essential aspects of quantum mechanics. At the close of each lecture, Fermi created a single problem for his students. These challenging exercises were not included in Fermi's notes but were preserved in the notes of his students. This second edition includes a set of these assigned problems as compiled by one of his former students, Robert A. Schluter. Enrico Fermi was awarded the Nobel Prize for Physics in 1938.
Indian Standard Code Of Practice Is-456 For The Design Of Main And Reinforced Concrete Was Revised In The Year 2000 To Incorporate Durability Criteria In The Design. As A Result Of It Many Codal Provisions Have Been Changed. Hence There Is Need To Train Engineering Students In Designing Reinforced Cement Concrete Structures As Per The Latest Code Of Is -456. With His Experience Of More Than 40 Years In Teaching, The Author Has Tried To Bring Out Students And Teachers Friendly Book On The Design Of Rcc Structures As Per Is-456: 2000.Rcc Design Is A Vast Subject. It Is Normally Taught In Two To Three Courses For Civil Engineering Students. This Book Is For The First Course In Rcc Design And Author Is Writing Another Book Advanced Rcc Design To Meet The Requirement Of Further Courses. This Book Deals With Design Philosophy And Design Of Various Structural Components Of Building. The Design Procedure Is Clearly Explained And Illustrated With Several Examples By Presenting The Solutions Step By Step In Details And With Neat Sketches Showing Reinforcement Details.