We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    Leading networking authority Douglas Comer presents a wide-ranging, self-contained tour of the concepts, principles, and technologies that enable today's Internet to support applications ranging from web browsing to telephony and multimedia. This Fifth Edition has been thoroughly reorganized, revised, and updated: it includes extensive new coverage of topics ranging from wireless protocols to network performance, while reducing or eliminating coverage of older protocols and technologies. Comer begins by illuminating the applications and facilities offered by today's Internet. Next, he systematically introduces the underlying network technologies and protocols that make them possible: low-level data communications; packet switching, LAN, and WAN technologies; and Internet protocols such as TCP, IP, UDP, and IPv6. With these concepts and technologies established, he introduces several of the most important contemporary issues faced by network implementers and managers, including quality of service, Internet telephony, multimedia, network security, and network management. Comer has carefully designed this book to support both top-down and bottom-up teaching approaches. Students need no background in operating systems, and no sophisticated math: Comer relies throughout on figures, drawings, examples, and analogies, "not" mathematical proofs.

    Digital Design and Computer Architecture begins with a modern approach by rigorously covering the fundamentals of digital logic design and then introducing Hardware Description Languages (HDLs). Featuring examples of the two most widely-used HDLs, VHDL and Verilog, the first half of the text prepares the reader for what follows in the second: the design of a MIPS Processor. By the end of Digital Design and Computer Architecture, readers will be able to build their own microprocessor and will have a top-to-bottom understanding of how it works--even if they have no formal background in design or architecture beyond an introductory class. David Harris and Sarah Harris combine an engaging and humorous writing style with an updated and hands-on approach to digital design.Unique presentation of digital logic design from the perspective of computer architecture using a real instruction set, MIPS.Side-by-side examples of the two most prominent Hardware Design Languages--VHDL and Verilog--illustrate and compare the ways the each can be used in the design of digital systems.Worked examples conclude each section to enhance the reader's understanding and retention of the material.

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

    By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

    

    The gold standard for attaining security is cryptography because it provides the most reliable tools for storing or transmitting digital information. Written by Niels Ferguson, lead cryptographer for Counterpane, Bruce Schneier's security company, and Bruce Schneier himself, this is the much anticipated follow-up book to Schneier's seminal encyclopedic reference, Applied Cryptography, Second Edition (0-471-11709-9), which has sold more than 150,000 copies. Niels Ferguson (Amsterdam, Netherlands) is a cryptographic engineer and consultant at Counterpane Internet Security. He has extensive experience in the creation and design of security algorithms, protocols, and multinational security infrastructures. Previously, Ferguson was a cryptographer for DigiCash and CWI. At CWI he developed the first generation of off-line payment protocols. He has published numerous scientific papers. Bruce Schneier (Minneapolis, MN) is Founder and Chief Technical Officer at Counterpane Internet Security, a managed-security monitoring company. He is also the author of Secrets and Lies: Digital Security in a Networked World (0-471-25311-1).

    By the end of the book, you'll understand how to develop a large, maintainable, and performant application with AngularJS.Guided by two engineers who worked on AngularJS at Google, you'll learn the components needed to build data-driven applications, using declarative programming and the Model-view-controller pattern. You'll also learn how to conduct unit tests on each part of your application.Learn how to use controllers for moving data to and from viewsUnderstand when to use AngularJS services instead of controllersCommunicate with the server to store, fetch, and update data asynchronouslyKnow when to use AngularJS filters for converting data and values to different formatsImplement single-page applications, using ngRoute to select views and navigationDive into basic and advanced directives for creating reusable componentsWrite an end-to-end test on a live version of your entire applicationUse best practices, guidelines, and tools throughout the development cycle

    The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms. In the second edition, besides revisions to the first edition, a number of new exercises have been added.

    Readers learn how to reduce time constraints and develop programs efficiently by analyzing the feasibility of an algorithm before it is coded. The C++ language is brought up-to-date and simplified, and the Standard Template Library is now fully incorporated throughout the text. This Third Edition also features significantly revised coverage of lists, stacks, queues, and trees and an entire chapter dedicated to amortized analysis and advanced data structures such as the Fibonacci heap. Known for its clear and friendly writing style, Data Structures and Algorithm Analysis in C++ is logically organized to cover advanced data structures topics from binary heaps to sorting to NP-completeness. Figures and examples illustrating successive stages of algorithms contribute to Weiss' careful, rigorous and in-depth analysis of each type of algorithm.

    From Mary, Queen of Scots, trapped by her own code, to the Navajo Code Talkers who helped the Allies win World War II, to the incredible (and incredibly simple) logisitical breakthrough that made Internet commerce secure, The Code Book tells the story of the most powerful intellectual weapon ever known: secrecy.Throughout the text are clear technical and mathematical explanations, and portraits of the remarkable personalities who wrote and broke the world’s most difficult codes. Accessible, compelling, and remarkably far-reaching, this book will forever alter your view of history and what drives it. It will also make you wonder how private that e-mail you just sent really is.

    Many exercises are presented to help reinforce the lessons learned, and answers to the exercises are given in a new appendix.Most of the remaining chapters are dedicated to the reference material, which describes in detail the standard features of Scheme included in the Revised$^5$ Report on Scheme and the ANSI/IEEE standard for Scheme.Numerous examples are presented throughout the introductory and reference portions of the text, and a unique set of extended example programs and applications, with additional exercises, are presented in the final chapter. Reinforcing the book's utility as a reference text are appendices that present the formal syntax of Scheme, a summary of standard forms and procedures, and a bibliography of Scheme resources.The Scheme Programming Language stands alone as an introduction to and essential reference for Scheme programmers. it is also useful as a supplementary text for any course that uses Scheme.The Scheme Programming Language is illustrated by artist Jean-Pierre Hébert, who writes Scheme programs to extend his ability to create sophisticated works of digital art.R. Kent Dybvig is Professor of Computer Science at Indiana University and principal developer of Chez Scheme.

    In eight chapters, it provides the most thorough coverage of TCP available. It also covers the newest TCP/IP features, including multicasting, path MTU discovery and long fat pipes. The author describes various protocols, including ARP, ICMP and UDP. He utilizes network diagnostic tools to actually show the protocols in action. He also explains how to avoid silly window syndrome (SWS) by using numerous helpful diagrams. This book gives you a broader understanding of concepts like connection establishment, timeout, retransmission and fragmentation. It is ideal for anyone wanting to gain a greater understanding of how the TCP/IP protocols work.