Download or read book Elements of ML Programming written by Jeffrey D. Ullman and published by Pearson. This book was released on 1998-01 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly accessible introduction to the fundamentals of ML is presented by computer science educator and author, Jeffrey D. Ullman. The primary change in the Second Edition is that it has been thoroughly revised and reorganized to conform to the new language standard called ML97. This is the first book that offers both an accurate step-by-step tutorial to ML programming and a comprehensive reference to advanced features. It is the only book that focuses on the popular SML/NJ implementation. The material is arranged for use in sophomore through graduate level classes or for self-study. This text assumes no previous knowledge of ML or functional programming, and can be used to teach ML as a first programming language. It is also an excellent supplement or reference for programming language concepts, functional programming, or compiler courses.
Download or read book Elements of ML Programming written by Jeffrey D. Ullman and published by . This book was released on 1998 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by renowned computer science educator and researcher Jeffrey Ullman, this text assumes no previous knowledge of ML or functional programming. This second edition has been heavily revised and updated using ML 97. This is the first book that offers BOTH a highly accessible, step-by-step introductory tutorial on ML programming and a complete explanation of advanced features. The author uses a wide variety of program examples to show how ML can be used in a variety of applications. More sophisticated programs and advanced concepts make this book usable in a number of courses for self-study or class discussion.* Summarizes the entire ML 97 language including the latest SML/NJ features. * The author, who is a data structure pioneer, shows how standard structures and problems (e.g., hashing, binary trees, solving linear equations, numerical integration, and sorting) are implemented with ML. * Makes ML programming interesting for the uninitiated. * Demonstrates the power and ease of functional programming with a variety of interesting small and large program examples . * Gives an and accurate overview of important ML syntax and semantic subtleties. * Uses pedagogy that highlights k
Download or read book Elements of ML Programming written by Jeffrey D. Ullman and published by . This book was released on 1994 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hybrid Logic and its Proof-Theory demonstrates that hybrid-logical proof-theory remedies the lack of uniformity in ordinary modal-logical proof systems. Various versions and proof systems for hybrid logic are considered, providing a detailed overview of the topic.
Download or read book Elements of ML Programming written by and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Elements of Functional Programming written by Chris Reade and published by Addison Wesley Publishing Company. This book was released on 1989 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software -- Programming Techniques.
Download or read book Introduction to Programming Using SML written by Michael R. Hansen and published by Addison-Wesley. This book was released on 1999 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on Hanson and Rischel's introductory programming course in the Informatics Programme at the Technical University of Denmark, Using Standard ML (Meta Language) throughout, they bypass theory and customized or efficient implementations to focus on understanding the process of programming and program design. Annotation copyrighted by Book News, Inc., Portland, OR
Download or read book The Definition of Standard ML written by Robin Milner and published by MIT Press. This book was released on 1997 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software -- Programming Languages.
Download or read book ML for the Working Programmer written by Lawrence C. Paulson and published by . This book was released on 1992 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition of a successful text treats modules in more depth, and covers the revision of ML language.
Download or read book Elements of Programming written by Alexander Stepanov and published by Lulu.com. This book was released on 2019-06-27 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of Programming provides a different understanding of programming than is presented elsewhere. Its major premise is that practical programming, like other areas of science and engineering, must be based on a solid mathematical foundation. The book shows that algorithms implemented in a real programming language, such as C++, can operate in the most general mathematical setting. For example, the fast exponentiation algorithm is defined to work with any associative operation. Using abstract algorithms leads to efficient, reliable, secure, and economical software.
Download or read book Functional Programming Using Standard ML written by Åke Wikström and published by . This book was released on 1987 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Download or read book Elements of Programming Interviews written by Adnan Aziz and published by EPI. This book was released on 2012 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: The core of EPI is a collection of over 300 problems with detailed solutions, including 100 figures, 250 tested programs, and 150 variants. The problems are representative of questions asked at the leading software companies. The book begins with a summary of the nontechnical aspects of interviewing, such as common mistakes, strategies for a great interview, perspectives from the other side of the table, tips on negotiating the best offer, and a guide to the best ways to use EPI. The technical core of EPI is a sequence of chapters on basic and advanced data structures, searching, sorting, broad algorithmic principles, concurrency, and system design. Each chapter consists of a brief review, followed by a broad and thought-provoking series of problems. We include a summary of data structure, algorithm, and problem solving patterns.
Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Download or read book An Introduction to Functional Programming Through Lambda Calculus written by Greg Michaelson and published by Courier Corporation. This book was released on 2013-04-10 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Well-respected text for computer science students provides an accessible introduction to functional programming. Cogent examples illuminate the central ideas, and numerous exercises offer reinforcement. Includes solutions. 1989 edition.
Download or read book Elementary Standard ML written by G Michaelson and published by CRC Press. This book was released on 2018-10-08 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with programming in the language Standard ML (SML), that is using SML to make precise models for computer animation. It draws on the distinction between programming in the small and in the large, plumping exclusively for the former.
Download or read book The Standard ML Basis Library written by Emden R. Gansner and published by Cambridge University Press. This book was released on 2004-04-05 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a description of the Standard ML (SML) Basis Library, the standard library for the SML language. For programmers using SML, it provides a complete description of the modules, types and functions composing the library, which is supported by all conforming implementations of the language. The book serves as a programmer's reference, providing manual pages with concise descriptions. In addition, it presents the principles and rationales used in designing the library, and relates these to idioms and examples for using the library. A particular emphasis of the library is to encourage the use of SML in serious system programming. Major features of the library include I/O, a large collection of primitive types, support for internationalization, and a portable operating system interface. This manual will be an indispensable reference for students, professional programmers, and language designers.
Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
