Master the art of machine learning with Python and build effective machine learning systems with this intensive hands-on guide Overview …
A large international conference on Advances in Machine Learning and Systems Engineering was held in UC Berkeley, California, USA, October …
Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through …
Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and …
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to …
To really learn data science, you should not only master the tools—data science libraries, frameworks, modules, and toolkits—but also understand …
The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important …
Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts …
THIS TEXTBOOK is about computer science. It is also about Python. However, there is much more. The study of algorithms …
2nd ed. — Franklin, Beedle & Associates, September 22, 2013. — 240 p.This textbook is about computer science. It is …
Create, train, and evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity Framework, and ASP.NET …
Data Structures and Algorithm Analysis in Java is an “advanced algorithms” book that fits between traditional CS2 and Algorithms Analysis …
Все больше и больше программистов обращаются к языку Python, и эта книга даст им понимание того, что им нужно. Автор …
THIS BOOK is intended for use in a traditional college-level data structures course (commonly known as CS2). This book assumes …
This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented …
Kalman and Wiener Filters, Neural Networks, Genetic Algorithms and Fuzzy Logic Systems Together in One Text Book How can a …
Li (geo-informatics, Hong Kong Polytechnic U.), Zhu (information engineering, Wuhan U.), and Gold's (computing, U. of Glamorgan) textbook is a …
The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural …
Industrial robots carry out simple tasks in customized environments for which it is typical that nearly all e?ector movements can …
Designing distributed computing systems is a complex process requiring a solid understanding of the design problems and the theoretical and …
The 16th International Symposium on Fundamentals of Computation Theory was held in Budapest, Hungary, in August 2007. This symposium drew …
Lewis and Papadimitriou present this long awaited Second Edition of their best-selling theory of computation. The authors are well-known for …
There has been a common perception that computational complexity is a theory of "bad news" because its most typical results …
This book offers a comprehensive perspective to modern topics in complexity theory, which is a central field of the theoretical …
This book contains a revised version of the dissertation the author wrote at the Department of Computer Science of the …
A computational model is a framework for doing computations according to certain specified rules on some input data. These models …
This book deals with the computational complexity of mathematical problems for which available information is partial, noisy and priced. The …
The book "Computational Error and Complexity in Science and Engineering" pervades all the science and engineering disciplines where computation occurs. …
The bible of all fundamental algorithms and the work that taught many of today's software developers most of what they …
The Art of Computer Programming, Volume 4A: Combinatorial Algorithms, Part 1 Knuth’s multivolume analysis of algorithms is widely recognized as …
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