Machine learning allows computational systems to adaptively improve their performance with experience accumulated from the observed data. Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

How do groups of neurons interact to enable the organism to see, decide, and move appropriately? What are the principles whereby networks of neurons represent and compute? These are the central questions probed by The Computational Brain. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework.Computer models constrained by neurobiological data can help reveal how -networks of neurons subserve perception and behavior - bow their physical interactions can yield global results in perception and behavior, and how their physical properties are used to code information and compute solutions. The Computational Brain focuses mainly on three domains: visual perception, learning and memory, and sensorimotor integration. Examples of recent computer models in these domains are discussed in detail, highlighting strengths and weaknesses, and extracting principles applicable to other domains. Churchland and Sejnowski show how both abstract models and neurobiologically realistic models can have useful roles in computational neuroscience, and they predict the coevolution of models and experiments at many levels of organization, from the neuron to the system.The Computational Brain addresses a broad audience: neuroscientists, computer scientists, cognitive scientists, and philosophers. It is written for both the expert and novice. A basic overview of neuroscience and computational theory is provided, followed by a study of some of the most recent and sophisticated modeling work in the context of relevant neurobiological research. Technical terms are clearly explained in the text, and definitions are provided in an extensive glossary. The appendix contains a precis of neurobiological techniques.Patricia S. Churchland is Professor of Philosophy at the University of California, San Diego, Adjunct Professor at the Salk Institute, and a MacArthur Fellow. Terrence J. Sejnowski is Professor of Biology at the University of California, San Diego, Professor at the Salk Institute, where he is Director of the Computational Neurobiology Laboratory, and an Investigator of the Howard Hughes Medical Institute.

Graphical models, a marriage between probability theory and graph theory, provide a natural tool for dealing with two problems that occur throughout applied mathematics and engineering--uncertainty and complexity. In particular, they play an increasingly important role in the design and analysis of machine learning algorithms. Fundamental to the idea of a graphical model is the notion of modularity: a complex system is built by combining simpler parts. Probability theory serves as the glue whereby the parts are combined, ensuring that the system as a whole is consistent and providing ways to interface models to data. Graph theory provides both an intuitively appealing interface by which humans can model highly interacting sets of variables and a data structure that lends itself naturally to the design of efficient general-purpose algorithms.This book presents an in-depth exploration of issues related to learning within the graphical model formalism. Four chapters are tutorial chapters--Robert Cowell on Inference for Bayesian Networks, David MacKay on Monte Carlo Methods, Michael I. Jordan et al. on Variational Methods, and David Heckerman on Learning with Bayesian Networks. The remaining chapters cover a wide range of topics of current research interest.

About This Book
Design, simulate, build and program an interactive autonomous mobile robotProgram Robot Operating System using PythonGet a grip on the hands-on guide to robotics for learning various robotics concepts and build an advanced robot from scratch
Who This Book Is For
If you are an engineer, a researcher, or a hobbyist, and you are interested in robotics and want to build your own robot, this book is for you. Readers are assumed to be new to robotics but should have experience with Python.
What You Will Learn
Understand the core concepts and terminologies of robotics Create 2D and 3D drawings of robots using freeware such as LibreCAD and Blender Simulate your robot using ROS and Gazebo Build robot hardware from the requirements Explore a diverse range of actuators and its interfacing Interface various robotic sensors to robots Set up and program OpenCV, OpenNI, and PCL to process 2D/3D visual data Learn speech processing and synthesis using Python Apply artificial intelligence to robots using Python Build a robot control GUI using Qt and Python Calibration and testing of robot
In Detail
Learning about robotics will become an increasingly essential skill as it becomes a ubiquitous part of life. Even though robotics is a complex subject, several other tools along with Python can help you design a project to create an easy-to-use interface.
Learning Robotics Using Python is an essential guide for creating an autonomous mobile robot using popular robotic software frameworks such as ROS using Python. It also discusses various robot software frameworks and how to go about coding the robot using Python and its framework. It concludes with creating a GUI-based application to control the robot using buttons and slides.
By the end of this tutorial, you'll have a clear idea of how to integrate and assemble all things into a robot and how to bundle the software package.

What happens to our conception of mind and rational agency when we take seriously future-directed intentions and plans and their roles as inputs into further practical reasoning? The author's initial efforts in responding to this question resulted in a series of papers that he wrote during the early 1980s. In this book, Bratman develops further some of the main themes of these essays and also explores a variety of related ideas and issues. He develops a planning theory of intention. Intentions are treated as elements of partial plans of action. These plans play basic roles in practical reasoning, roles that support the organization of our activities over time and socially. Bratman explores the impact of this approach on a wide range of issues, including the relation between intention and intentional action, and the distinction between intended and expected effects of what one intends.

With contributions by Michael Ashikhmin, Michael Gleicher, Naty Hoffman, Garrett Johnson, Tamara Munzner, Erik Reinhard, Kelvin Sung, William B. Thompson, Peter Willemsen, Brian Wyvill.
The third edition of this widely adopted text gives students a comprehensive, fundamental introduction to computer graphics. The authors present the mathematical foundations of computer graphics with a focus on geometric intuition, allowing the programmer to understand and apply those foundations to the development of efficient code.
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New in this edition:
* Four new contributed chapters, written by experts in their fields: Implicit Modeling, Computer Graphics in Games, Color, Visualization, including information visualization
* Revised and updated material on the graphics pipeline, reflecting a modern viewpoint organized around programmable shading.
* Expanded treatment of viewing that improves clarity and consistency while unifying viewing in ray tracing and rasterization.
* Improved and expanded coverage of triangle meshes and mesh data structures.
A new organization for the early chapters, which concentrates foundational material at the beginning to increase teaching flexibility.

This book provides a fundamental understanding of global illumination algorithms. It discusses a broad class of algorithms for realistic image synthesis and introduces a theoretical basis for the algorithms presented. Topics include: physics of light transport, Monte Carlo methods, general strategies for solving the rendering equation, stochastic path-tracing algorithms such as ray tracing and light tracing, stochastic radiosity including photon density estimation and hierarchical Monte Carlo radiosity, hybrid algorithms, metropolis light transport, irradiance caching, photon mapping and instant radiosity, beyond the rendering equation, image display and human perception. If you want to design and implement a global illumination rendering system or need to use and modify an existing system for your specific purpose, this book will give you the tools and the understanding to do so.

Thoroughly revised, this third edition focuses on modern techniques used to generate synthetic three-dimensional images in a fraction of a second. With the advent or programmable shaders, a wide variety of new algorithms have arisen and evolved over the past few years.
This edition discusses current, practical rendering methods used in games and other applications. It also presents a solid theoretical framework and relevant mathematics for the field of interactive computer graphics, all in an approachable style.

"In this second edition of Extreme Programming Explained, Kent Beck organizes and presents five years' worth of experiences, growth, and change revolving around XP. If you are seriously interested in understanding how you and your team can start down the path of improvement with XP, you must read this book." -Francesco Cirillo, Chief Executive Officer, XPLabs S.R.L. "The first edition of this book told us what XP was-it changed the way many of us think about software development. This second edition takes it farther and gives us a lot more of the 'why' of XP, the motivations and the principles behind the practices. This is great stuff. Armed with the 'what' and the 'why,' we can now all set out to confidently work on the 'how': how to run our projects better, and how to get agile techniques adopted in our organizations." -Dave Thomas, The Pragmatic Programmers LLC "This book is dynamite! It was revolutionary when it first appeared a few years ago, and this new edition is equally profound. For those who insist on cookbook checklists, there's an excellent chapter on 'primary practices,' but I urge you to begin by truly contemplating the meaning of the opening sentence in the first chapter of Kent Beck's book: 'XP is about social change.' You should do whatever it takes to ensure that every IT professional and every IT manager-all the way up to the CIO-has a copy of Extreme Programming Explained on his or her desk." -Ed Yourdon, author and consultant "XP is a powerful set of concepts for simplifying the process of software design, development, and testing. It is about minimalism and incrementalism, which are especially useful principles when tackling complex problems that require a balance of creativity and discipline." -Michael A. Cusumano, Professor, MIT Sloan School of Management, and author of The Business of Software"Extreme Programming Explained is the work of a talented and passionate craftsman. Kent Beck has brought together a compelling collection of ideas about programming and management that deserves your full attention. My only beef is that our profession has gotten to a point where such common-sense ideas are labeled 'extreme.'..." -Lou Mazzucchelli, Fellow, Cutter Business Technology Council"If your organization is ready for a change in the way it develops software, there's the slow incremental approach, fixing things one by one, or the fast track, jumping feet first into Extreme Programming. Do not be frightened by the name, it is not that extreme at all. It is mostly good old recipes and common sense, nicely integrated together, getting rid of all the fat that has accumulated over the years." -Philippe Kruchten, UBC, Vancouver, British Columbia"Sometimes revolutionaries get left behind as the movement they started takes on a life of its own. In this book, Kent Beck shows that he remains ahead of the curve, leading XP to its next level. Incorporating five years of feedback, this book takes a fresh look at what it takes to develop better software in less time and for less money. There are no silver bullets here, just a set of practical principles that, when used wisely, can lead to dramatic improvements in software development productivity." -Mary Poppendieck, author of Lean Software Development: An Agile Toolkit "Kent Beck has revised his classic book based on five more years of applying and teaching XP. He shows how the path to XP is both easy and hard: It can be started with fewer practices, and yet it challenges teams to go farther than ever." -William Wake, independent consultant "With new insights, wisdom from experience, and clearer explanations of the art of Extreme Programming, this edition of Beck's classic will help many realize the dream of outstanding software development." -Joshua Kerievsky, author of Refactoring to Patterns and Founder, Industrial Logic, Inc."XP has changed the way our industry thinks about software development. Its brilliant simplicity, focused execution, and insistence on fact-based planning over speculation have set a new standard for software delivery." -David Trowbridge, Architect, Microsoft Corporation Accountability. Transparency. Responsibility. These are not words that are often applied to software development. In this completely revised introduction to Extreme Programming (XP), Kent Beck describes how to improve your software development by integrating these highly desirable concepts into your daily development process. The first edition of Extreme Programming Explained is a classic. It won awards for its then-radical ideas for improving small-team development, such as having developers write automated tests for their own code and having the whole team plan weekly. Much has changed in five years. This completely rewritten second edition expands the scope of XP to teams of any size by suggesting a program of continuous improvement based on: * Five core values consistent with excellence in software development * Eleven principles for putting those values into action * Thirteen primary and eleven corollary practices to help you push development past its current business and technical limitations Whether you have a small team that is already closely aligned with your customers or a large team in a gigantic or multinational organization, you will find in these pages a wealth of ideas to challenge, inspire, and encourage you and your team members to substantially improve your software development. You will discover how to: * Involve the whole team-XP style * Increase technical collaboration through pair programming and continuous integration * Reduce defects through developer testing * Align business and technical decisions through weekly and quarterly planning * Improve teamwork by setting up an informative, shared workspace You will also find many other concrete ideas for improvement, all based on a philosophy that emphasizes simultaneously increasing the humanity and effectiveness of software development. Every team can improve. Every team can begin improving today. Improvement is possible-beyond what we can currently imagine. Extreme Programming Explained, Second Edition, offers ideas to fuel your improvement for years to come.

With the same insight and authority that made their book The Unix Programming Environment a classic, Brian Kernighan and Rob Pike have written The Practice of Programming to help make individual programmers more effective and productive. This book is full of practical advice and real-world examples in C, C++, Java, and a variety of special-purpose languages. Kernighan and Pike have distilled years of experience writing programs, teaching, and working with other programmers to create this book. Anyone who writes software will profit from its principles and guidance.

"There are books--few and far between--which carefully, delightfully, and genuinely turn your head inside out. This is one of them. It ranges over some central issues in Western philosophy and begins the long overdue job of giving us a radically new account of meaning, rationality, and objectivity."--Yaakov Garb, San Francisco Chronicle

In "The Meaning of the Body", Mark Johnson continues his pioneering work on the exciting connections between cognitive science, language, and meaning first begun in the classic "Metaphors We Live By". Johnson uses recent research into infant psychology to show how the body generates meaning even before self-consciousness has fully developed. From there he turns to cognitive neuroscience to further explore the bodily origins of meaning, thought, and language and examines the many dimensions of meaning - including images, qualities, emotions, and metaphors - that are all rooted in the body's physical encounters with the world. Drawing on the psychology of art and pragmatist philosophy, Johnson argues that all of these aspects of meaning-making are fundamentally aesthetic. He concludes that the arts are the culmination of human attempts to find meaning and that studying the aesthetic dimensions of our experience is crucial to unlocking meaning's bodily sources.Throughout, Johnson puts forth a bold new conception of the mind rooted in the understanding that philosophy will matter to nonphilosophers only if it is built on a visceral connection to the world.

One of the leading textbooks on Haskell programming, this third edition is thoroughly revised throughout and includes new material on testing and domain-specific languages and a variety of new examples and case studies, including simple games.
* Emphasises software engineering principles.
* Encourages a disciplined approach to building reusable libraries of software components.
* Case studies are used throughout the book to introduce new ideas, illustrate important concepts, and demonstrate how existing techniques work together. Case studies include:
- An interactive calculator programme.
- A coding and decoding system.
- A small queue simulation package.
* Companion website contains supporting material (such as visualisation tools * and a substantial number of web links) to aid further study.
Appendices contain information on Hugs errors.

This book teaches functional programming as a way of thinking and problem solving, using Haskell, the most popular purely functional language. Rather than using the conventional mathematical examples commonly found in other programming language textbooks, the author draws examples from multimedia applications, including graphics, animation, and computer music, thus rewarding the reader with working programs for inherently more interesting applications. Aimed at both beginning and advanced programmers, this tutorial begins with a gentle introduction to functional programming and moves rapidly on to more advanced topics. An underlying theme is the design and implementation of domain specific languages, using three examples: FAL (a Functional Animation Language), IRL (an Imperative Robot Language), and MDL (a Music Description Language). Details about programming in Haskell are presented in boxes throughout the text so they can be easily referred to and found quickly.

Hacking your program is no substitute for understanding your problem. Prolog is different, but not that different. Elegance is not optional. These are the themes that unify Richard O'Keefe's very personal statement on how Prolog programs should be written. The emphasis in The Craft of Prolog is on using Prolog effectively. It presents a loose collection of topics that build on and elaborate concepts learned in a first course. These may be read in any order following the first chapter, "Basic Topics in Prolog," which provides a basis for the rest of the material in the book.Richard A. O'Keefe is Lecturer in the Department of Computer Science at the Royal Melbourne Institute of Technology. He is also a consultant to Quintus Computer Systems, Inc.Contents: Basic Topics in Prolog. Searching. Where Does the Space Go? Methods of Programming. Data Structure Design. Sequences. Writing Interpreters. Some Notes on Grammar Rules. Prolog Macros. Writing Tokenisers in Prolog. All Solutions.

A comprehensive introduction to type systems and programming languages. A type system is a syntactic method for automatically checking the absence of certain erroneous behaviors by classifying program phrases according to the kinds of values they compute. The study of type systems—and of programming languages from a type-theoretic perspective—has important applications in software engineering, language design, high-performance compilers, and security. This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material. The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.