Here is the essential guide to computers, an authoritative reference book and timeline about the most powerful tools ever devised. Computing has been the sharp end of cutting-edge technology for a generation and it now permeates all our lives. But to many computer science remains something of a mystery. Our story begins long before the silicon chip, when the pinnacle of binary code was found in the Chinese I-Ching, when Algorithm was a man from Baghdad, and when Lord Byron's daughter wrote the first software--in ink. Above all the first computers were humans, but today they are anything but. Our journey hacks through the jargon jungle of blockchains, botnets, and bitcoins, to arrive at the latest computing technologies, which will no doubt be changing our world all over again.

• Contains chronological articles that tell the story of computers through 100 discoveries and inventions.
• A guide to computer science demystifies the subject, setting out the basics with light-hearted text and simple diagrams.
• Includes biographies of the great computer scientists, such as Babbage, Turing, and Berners-Lee.
• A series of infographics presenting the mind-boggling facts and figures of modern computing at a glance also boosts the contents for all readers.
• Includes a 12-page foldout Timeline poster which stretches out to 8.5 feet (2.6 meters) long.

Correlation is not causation. This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.

Advances in Generative Artificial Intelligence (GAI) have created a new class of computer systems that exhibit astonishing proficiency on a wide variety of tasks with superhuman performance, producing novel text, images, music, and software by analyzing enormous collections of digitized information. Soon, these systems will provide expert medical care; offer legal advice; draft documents; write computer programs; tutor our children; and generate music and art. These advances will accelerate progress in science, art, and human knowledge, but they will also bring new dangers.

Have we finally discovered the holy grail of AI - machines that match or exceed human intelligence? Which industries and professions will thrive, and which will wither? What risks and dangers will it pose? How can we ensure that these systems respect our ethical principles? Will the benefits be broadly distributed or accrue to a lucky few? How will GAI alter our political systems and international conflicts? Are we merely a stepping stone to a new form of non-biological life, or are we just getting better at building useful gadgets?

Generative Artificial Intelligence: What Everyone Needs to Know(R) equips readers with the knowledge to answer these pressing questions.

This is the fourth edition of Distributed Systems. We have stayed close to the setup of the third edition, including examples of (part of) existing distributed systems close to where general principles are discussed. For example, we have included material on blockchain systems, and discuss their various components throughout the book. We have, again, used special boxed sections for material that can be skipped at first reading.

The text has been thoroughly reviewed, revised, and updated. In particular, all the Python code has been updated to Python3, while at the same time the channel package has been almost completely revised and simplified.

Additional material, including coding examples, figures, and slides, are available at www.distributed-systems.net.

What will you learn from this book?

You know you don't want to reinvent the wheel, so you look to Design Patterns: the lessons learned by those who've faced the same software design problems. With Design Patterns, you get to take advantage of the best practices and experience of others so you can spend your time on something more challenging. Something more fun. This book shows you the patterns that matter, when to use them and why, how to apply them to your own designs, and the object-oriented design principles on which they're based. Join hundreds of thousands of developers who've improved their object-oriented design skills through Head First Design Patterns.

What's so special about this book?

If you've read a Head First book, you know what to expect: a visually rich format designed for the way your brain works. With Head First Design Patterns, 2E you'll learn design principles and patterns in a way that won't put you to sleep, so you can get out there to solve software design problems and speak the language of patterns with others on your team.

As a concept, Artificial Intelligence has fueled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. In this Very Short Introduction, Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative, or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible.

ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

A walkthrough of computer science concepts you must know. Designed for readers who don't care for academic formalities, it's a fast and easy computer science guide. It teaches the foundations you need to program computers effectively. After a simple introduction to discrete math, it presents common algorithms and data structures. It also outlines the principles that make computers and programming languages work.

Every great programming challenge has mathematical principles at its heart. Whether you're optimizing search algorithms, building physics engines for games, or training neural networks, success depends on your grasp of core mathematical concepts.

In Math for Programming, you'll master the essential mathematics that will take you from basic coding to serious software development. You'll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms.

Through clear explanations and practical examples, you'll learn to:

• Harness linear algebra to manipulate data with unprecedented efficiency
• Apply calculus concepts to optimize algorithms and drive simulations
• Use probability and statistics to model uncertainty and analyze data
• Master the discrete mathematics that powers modern data structures
• Solve dynamic problems through differential equations

You know how to code...

...but is it enough?

Do you feel left out when other programmers talk about amortized runtime?

Have you failed a job interview because you don't know computer science?

Volume two picks up where volume one left off. It covers more advanced topics, including:

• Proofs
• Security
• Hardware and software
• Operating systems
• Networks
• Databases
• And much more

You've learned the basics. Are you ready for what comes next?

Introduction to Artificial Intelligence is not just a book; it's a comprehensive educational experience designed to bring you to the forefront of AI knowledge. This guide opens the door to the transformative world of AI, emphasizing its significance in today's society. It offers an inclusive welcome, setting the stage for readers from all backgrounds and delves into how AI reshapes our modern world.

As we traverse the historical landscape of AI, from the musings of ancient philosophers to the breakthroughs of the digital era, you'll gain a deep understanding of the field's roots and evolution. The book outlines the shift from Symbolic AI's rigid logic to the fluid learning of modern neural networks, illuminated by interactive quizzes that reinforce learning and comprehension.

The core chapters provide a deep dive into the technical aspects of AI, covering key concepts and subfields with an engaging mix of theory and hands-on learning. Each major branch of AI is accompanied by an online lab, inviting you to apply your knowledge in a practical, interactive environment.

By purchasing this book, you unlock access to an exclusive online course replete with instructional videos, quizzes, and online labs that echo the book's content, allowing you to solidify your understanding and apply concepts in a dynamic way. This blended learning approach ensures you not only read about AI but also practice and experience it firsthand.

The discussion on ethics prepares you to navigate the complex moral landscape AI presents, while real-world applications and case studies showcase AI's practical impact. The book also peers into the future, predicting how AI will continue to evolve and shape our world.

For those looking to turn curiosity into expertise, Introduction to Artificial Intelligence outlines clear educational pathways and career advice, supported by a wealth of resources and a community of fellow AI enthusiasts through Destin Learning.

Concluding with insights from the author and further learning opportunities, including the Destin Learning YouTube Channel, this book is your gateway to becoming part of the AI revolution. It's an essential resource for students, professionals, and anyone eager to understand and harness the power of artificial intelligence.

Algorithms are the heart and soul of computer science. Their applications range from network routing and computational genomics to public-key cryptography and machine learning. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subject for anyone with at least a little programming experience. The exposition emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details---like a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. Part 2 covers graph search and applications, shortest paths, and the usage and implementation of several data structures (heaps, search trees, hash tables, and bloom filters).

A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation. Eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, computational thinking has become part of the K-12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview--tracing a genealogy that begins centuries before digital computers and portraying computational thinking as the pioneers of computing have described it.

The authors explain that computational thinking (CT) is not a set of concepts for programming; it is a way of thinking that is honed through practice: the mental skills for designing computations to do jobs for us, and for explaining and interpreting the world as a complex of information processes. Mathematically trained experts (known as computers) who performed complex calculations as teams engaged in CT long before electronic computers. In each chapter, the author identify different dimensions of today's highly developed CT:

- Computational Methods
- Computing Machines
- Computing Education
- Software Engineering
- Computational Science
- Design

Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.

Algorithms are the heart and soul of computer science. Their applications range from network routing and computational genomics to public-key cryptography and machine learning. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subject for anyone with at least a little programming experience. The exposition emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details---like a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. Part 3 covers greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, shortest paths, optimal search trees).

- Quantum bits, or qubits--the basic unit of quantum computing
- Quantum entanglement and what it means when qubits are entangled
- Quantum cryptography
- Classical computing topics like bits, gates, and logic
- Quantum gates
- Quantum algorithms and their speed
- Quantum computers and how they're built
- And more!

By the end of the book, readers understand that quantum computing and classical computing are not two distinct disciplines, and that quantum computing is the fundamental form of computing.

How to become a computer programming master without the hassle of taking a course, all while in the comfort of your own home.

In today's technologically-dominated world, it's only natural to become interested in the workings of computers and ponder on the idea of developing your very own app or game.

Who knows, maybe you have had a million-dollar idea planned out in your mind for a while now, but every time you think about acting on it, reality hits you with the fact that there's one huge obstacle in your way:

You don't know how to code.

Well actually, it may feel like a huge obstacle, but with the right expert guidance, it s like following the Lego building instructions for 6-year-olds.

By exploring all that computer programming has to offer, it opens a whole new world of possibilities you may not have known existed. Knowing how to code is the magical key to:

• Developing apps
• Creating softwares
• Constructing websites
• Designing fun, addicting games
• Or just as a new hobby

Did you know that the top 200 apps generate on average $82,500 daily?

Whether your incentive to learn about computer programming stems from interest, or it's because you want more work freedom and higher qualifications for a better paying job, starting with the basics and working your way up is the most promising approach to take.

In Computer Programing Bible, you will discover:

• A step by step guidance from beginner to advanced level to never get lost in signs and numbers
• The major programming languages essential to mastering code
• Why everyone in today's technology-driven world needs to know how to code if they don t want to be left behind
• 7 reasons why diving into the world of programming will change your life path in less than 6 months
• The key to writing your very first program even if you are a technophobe
• How to choose the best programming language to reach optimal results
• The all-too-common programming mistakes to avoid
• The unspoken challenges to be aware of that each programming language may present and how to overcome them

And much more.

Don't worry. This may seem like too much to handle right now, but rest assured, the sections are broken up into bite-size nuggets of knowledge designed to make understanding computer programming a breeze.

Even if you've never stepped foot into the how-to's of coding before and have absolutely no idea where to begin, you will be able to follow along step by step and soon become comfortable exploring it all on your own.

Programming must be a piece of cake if even 7-year-old Zora Ball managed to code her own full version of a video game.

The best is you can go at your own pace without the stress of a course where you waste money on something you can easily discover on your own.

But be aware: The Computer Programing Bible is only for people who know how to take action instead of joining the everlasting queue of procrastinators.

If you want to discover the unlimited potential computer programming has to offer and become your own digital boss, then scroll up and click the Add to Cart button right now.

This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.

The color images and text in this book have been converted to grayscale.

Mathematician Alan Turing invented an imaginary computer known as the Turing Machine; in an age before computers, he explored the concept of what it meant to be computable, creating the field of computability theory in the process, a foundation of present-day computer programming.

The book expands Turing's original 36-page paper with additional background chapters and extensive annotations; the author elaborates on and clarifies many of Turing's statements, making the original difficult-to-read document accessible to present day programmers, computer science majors, math geeks, and others.

Interwoven into the narrative are the highlights of Turing's own life: his years at Cambridge and Princeton, his secret work in cryptanalysis during World War II, his involvement in seminal computer projects, his speculations about artificial intelligence, his arrest and prosecution for the crime of gross indecency, and his early death by apparent suicide at the age of 41.