Ergebnis für "Algorithmen" in Informatik

From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

Algorithmen, die unser Leben beeinflussen, sind längst keine Zukunftsmusik mehr, sondern stecken überall tief in unserem Alltag. Sie unterstützen Ärztinnen und Ärzte bei der Diagnose, lassen die Vergangenheit bunt werden und Personen in Kinofilmen auftauchen, die gar nicht am Dreh waren. Im Hochleistungssport verraten sie, ob und warum sich Athleten und Athletinnen verletzen könnten und leiten uns mehr oder weniger offen durch digitale Welten - was entsprechende Sorgen vor unbewusster Manipulation weckt. Ein Spektrum Kompakt rund um programmierte Helfer im Hintergrund.

In Once Upon an Algorithm, Martin Erwig explains computation as something that takes place beyond electronic computers, and computer science as the study of systematic problem solving. Erwig points out that many daily activities involve problem solving. Getting up in the morning, for example: You get up, take a shower, get dressed, eat breakfast. This simple daily routine solves a recurring problem through a series of well-defined steps. In computer science, such a routine is called an algorithm.

Hilke Schellmann is an Emmy-award winning investigative reporter, Wall Street Journal and Guardian contributor and Journalism Professor at NYU. In The Algorithm, she investigates the rise of artificial intelligence (AI) in the world of work. AI is now being used to decide who has access to an education, who gets hired, who gets fired, and who receives a promotion. Drawing on exclusive information from whistleblowers, internal documents and real-world tests, Schellmann discovers that many of the algorithms making high-stakes decisions are biased, racist, and do more harm than good.

Ein sehr spannendes Thema in der heutigen Zeit! KI-Trading von A-Z, Geld verdienen mit Algorithmen, die Zukunft des TradingsKünstliche Intelligenz verändert die Finanzmärkte mit einer Wucht, die selbst erfahrene Trader staunen lässt. Maschinen analysieren Daten in Lichtgeschwindigkeit, treffen Entscheidungen autonom und formen eine neue Realität, in der traditionelle Handelsmethoden nicht mehr ausreichen. Dieses Buch zeigt, wie KI-Trading funktioniert, welche Mechanismen im Hintergrund wirken und warum menschlicher Instinkt gerade jetzt wichtiger ist als je zuvor.

Künstliche Intelligenz und Algorithmen erleichtern in Form von Navis, Rechtschreibprogrammen, Suchergänzungen oder Kaufempfehlungen schon lange unseren Alltag. Aber sie hinterlassen oft auch ein mulmiges Gefühl, weil wir nicht so recht verstehen, was da passiert. Katharina Zweig, IT-Expertin für Sozioinformatik und vielfach ausgezeichnete Informatikprofessorin, erklärt mit Witz und anhand einfacher Beispiele und Illustrationen, was Algorithmen eigentlich genau sind, wie sie funktionieren, welche völlig harmlos sind und welche uns tatsächlich Sorgen bereiten sollten.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

As artificial intelligence (AI) becomes more and more woven into our everyday lives—and underpins so much of the infrastructure we rely on—the ethical, security, and privacy implications require a critical approach that draws not simply on the programming and algorithmic foundations of the technology. Bringing together legal studies, philosophy, cybersecurity, and academic literature, Beyond the Algorithm examines these complex issues with a comprehensive, easy-to-understand analysis and overview.

Grokking Artificial Intelligence Algorithms is a fully illustrated and interactive tutorial guide to the different approaches and algorithms that underpin AI. Written in simple language and with lots of visual references and hands-on examples, you'll learn the concepts, terminology, and theory you need to effectively incorporate AI algorithms into your applications. And to make sure you truly grok as you go, you'll use each algorithm in practice with creative coding exercises.

Cutting through the noise of AI evangelists and AI doom-mongers, Wharton professor Ethan Mollick has become one of the most prominent and provocative explainers of AI, focusing on the practical aspects of how these new tools for thought can transform our world. In Co-Intelligence, he urges us to engage with AI as co-worker, co-teacher and coach.

Today, many decisions that could be made by human beings from predicting earthquakes to interpreting languages can now be made by computer algorithms with advanced analytic capabilities....Algorithms can better predict human behavior than trained psychologists and with much simpler criteria. Studies continue to show that the algorithms can do a better job than experts in a range of fields. Artificial intelligence is reshaping healthcare, science, engineering and life. The results will make our lives more productive, better organized, and essentially, much happier.

With artificial intelligence on the rise, the way we run our organisations will change - and drastically. But what exactly will that future look like? And who will take the leading role: Machines or people? In this compelling new audiobook, leading management guru David De Cremer identifies the key areas where algorithms will collide with human skills, and assesses the likely outcomes. The author presents fascinating insights into the challenges that an automated work environment poses for organisations of the future.

This audiobook narrated by Teri Schnaubelt explains how to put democracy at the heart of AI governance.

Algorithms of the Intelligent Web, Second Edition teaches you how to create machine learning applications that crunch and wrangle data collected from users, web applications, and website logs. In this totally revised edition, you'll look at intelligent algorithms that extract real value from data. Key machine learning concepts are explained with code examples in Python's scikit-learn. This book guides you through algorithms to capture, store, and structure data streams coming from the web.

In November 2022, OpenAI released GPT-4 in a chatbot form to the public. In just two months, it claimed 100 million users—the fastest app to ever reach this benchmark. Since then, AI has become an all-consuming topic, popping up on the news, in ads, on your messenger apps, and in conversations with friends and family. But as AI becomes ubiquitous and grows at an ever-increasing pace, what does it mean for the financial markets? MoneyGPT shows that the danger is not that AI will malfunction, but that it will function exactly as intended.

This book consists of 6 titles, namely: Assembly Language: The Ultimate Guide to Programming and Virtual Machines. Computer Science: The Complete Guide to Principles and Informatics. Cyber Security: Beginners’ Guide to Hacking, Phishing, Social Engineering, and Malware. Databases: System Concepts, Designs, Management, and Implementation. Operating Systems: Concepts to Save Money, Time, and Frustration. Website Development: Web Design Skills for Beginners

Every day, we use our computers to perform remarkable feats. A simple web search picks out a handful of relevant needles from the world's biggest haystack. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers, and we use digital signatures to verify the identity of the websites we visit.

The deep-learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep-learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

We are used to thinking of computers as being a step up from calculators - very good at storing information, and maybe even at playing a logical game like chess. But up to now they haven't been able to think in ways that are intuitive, or respond to questions as a human might. All that has changed, dramatically, in the past few years. Our search engines are becoming answer engines. Artificial intelligence is already revolutionising sectors from education to healthcare to the creative arts. But how does an AI understand sentiment or context?