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Post under Machine Learning on Sat Nov 25, 2017
This textbook provides a clear and simple account of the key ideas and algorithms of reinforcement learning that is accessible to readers in all the related disciplines. Familiarity with elementary concepts of probability is required.
The proliferation of inexpensive and highly mobile and location aware devices together with Web 2.0 technology have fostered the emergence of the citizen as a source of data. Mapping activities have benefitted greatly from advances in geoinformation technologies.
This book blends together the theories of GIS and their practical implementations in different conditions. It deals with GIS’s application in the broad spectrum of geospatial analysis and modeling, water resources analysis, land use analysis, and such.
Post under Machine Learning on Sat Nov 18, 2017
This is a set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.).
Post under Data Science on Sat Nov 18, 2017
This book provides non-technical readers with a gentle introduction to essential concepts and activities of data science. Provides explanations and code for a range of interesting applications using the open source R language for statistical computing and graphics.
Post under Statistics and Machine Learning on Sat Nov 04, 2017
This book aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. All the examples are implemented in the statistical programming language R.
The purpose of the book is to take a basic computer system and show you how every part works. It is taught from a technicians point of view, not an engineer’s. It covers electronic components, logic circuits, CPU, computer system, assembly language, etc.
This book introduces the concepts of functional and symbolic programming, applies these techniques to some problems of varying complexity, and eventually discusses the implementation of an abstraction layer for solving problems.
Defines the unique characteristics of cloud-native application architectures such as microservices and twelve-factor applications, and examines the cultural, organizational, and technical changes necessary to migrate to cloud-native architectures.
This booklet is a quick but thoughtful guide to jump into the Internet of Things (IoT), covering important subjects as IPv6 networking, sensors, wireless protocols and technologies, as well as IoT cloud platforms and its most commonly used protocols, etc.
This book focuses on the Discrete Fourier Transform (DFT), discrete convolution, and, particularly, the fast algorithms to calculate them. Topics on digital signal processing since its beginning, and new results in hardware, theory and applications, etc.
This book shows how to build better appliances – with more types of interfaces, more dynamic interfaces, and better debugged interfaces. You’ll learn how to build backend daemons, handle asynchronous events, and connect various user interfaces.
Aims to debunk that myth by showing how the finance industry can benefit from DevOps practices and perform a greater degree of automation by implementing DevOps properly. It explains DevOps benefits that are far more important for the financial services.
This is a book about prime numbers, congruences, secret messages, and elliptic curves that you can read cover to cover. Many numerical examples are given throughout the book using the Sage mathematical software.
This book, which presupposes familiarity only with the most elementary concepts of arithmetic (divisibility properties, greatest common divisor, etc.), is an expanded version of a series of lectures for graduate students on elementary number theory.