Ergebnis für "Big Data" in Informatik

Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases.  

The Age of Prediction is about two powerful, and symbiotic, trends: the rapid development and use of artificial intelligence and big data to enhance prediction, as well as the often paradoxical effects of these better predictions on our understanding of risk and the ways we live. Beginning with dramatic advances in quantitative investing and precision medicine, this book explores how predictive technology is quietly reshaping our world in fundamental ways, from crime fighting and warfare to monitoring individual health and elections.

We live in an incredible period in history. The computer revolution may be even more life-changing than the Industrial Revolution. We can do things with computers that could never be done before, and computers can do things for us that could never be done before. But our love of computers should not cloud our thinking about their limitations. The AI Delusion explains why we should not be intimidated into thinking that computers are infallible, that data-mining is knowledge discovery, and that black boxes should be trusted. 

This book will put AI, big data, the cloud, robotics, and smart devices in context. It will reveal how these technologies can dramatically multiply any businesses—including yours—by strategically using your data's latent, transformative potential.

"Big Data" is on the covers of Science, Nature, The Economist, and Wired magazines, on the front pages of the Wall Street Journal and The New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure.

What to Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on artificial intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans, it raises profound questions on the future of work and how companies compete.

In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally - hiring, driving, paying bills, even choosing romantic partners - that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology.

Three comprehensive manuscripts in one audiobook. Listen to this audiobook now if you want to learn more about machine learning!  

If you need to learn how to use machine learning, big data, data science, and neural networks but you can’t (or there is no time to) study the complicated math and algorithms behind these technologies, then keep reading. All technologies related to artificial intelligence represent an incredible opportunity if you want to grow your business or if you are searching for a new job, but it’s not very easy to understand how they work.

As we use the Web for social networking, shopping, and news, we leave a personal trail. These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion.

This book on machine learning will explain the concepts, methods, and history behind machine learning. Learn what it is, its importance, history, and much more.

Machines are able to interpret and understand human beings, and also interpret the data that is fed to them because of artificial intelligence. So, what is artificial intelligence? If you have been reading the basics, you will know that artificial intelligence is a human being’s attempt to make a machine smart enough to handle processes that a human being would normally do. It is not easy to do this, since you will need to understand the system and also learn the required programming languages to instruct the computer to behave in the required manner.

Data is a crucial commodity, increasing at an exponential rate. That Book on Big Data is a crash course covering big data, who’s using it, and its implications. From this audiobook you’ll learn definitions, techniques, and tools used by practitioners. Sampling the generators of data, and those hungrily consuming it, we dive into high profile use cases and those that fly under the radar. We’ll also consider personal implications of big data on everything (and everyone!). 

The computer world has acquired a wide range of sorts of individuals. Some are keen on making cash making their very own projects to offer to other people. Here, we will investigate somewhat about Python and why it is regularly favored over the other two programming alternatives. Machine learning is a use of artificial intelligence (AI) that gives software the capacity to naturally learn and improve without being unequivocally modified. Machine learning centers around the improvement of computer programs that can get to data and use it to learn for themselves. 

Artificial intelligence is the future, but it’s also a great opportunity today. You can use it to create incredible products with never seen before features. Probably, you are already using AI technologies in your everyday routine, and you don’t even know it! By the way, AI represents a significant opportunity if you want to grow your business or if you are searching for a new job, but it requires a solid background in terms of processes and technologies involved and, of course, you must fully understand how to implement AI in the business world.

Machine learning is a use of artificial intelligence (AI) that gives software the capacity to naturally learn and improve without being unequivocally modified. Machine learning centers around the improvement of computer programs that can get to data and use it to learn for themselves. The way toward learning starts with perceptions or data - for example, models, direct understanding, or guidance, so as to search for designs in data and settle on better choices later, depending on the models that we give.

Si usted está en la etapa de principiante y busca obtener nuevos conocimientos sobre el aprendizaje automático, entonces siga leyendo.... No escuche este audiolibro si usted está buscando un libro de texto aburrido que contenga mucha jerga de matemáticas y programación. Todos los días, alguien está renunciando a aprender sobre el aprendizaje automático. Muchas personas se pierden de continuar su carrera, y tal vez incluso el progreso de nuestra especie sin ni siquiera darse cuenta.

Today, 91 percent of Python programmers are not quite prepared. This is what the IT companies say, according to a recent survey. Do you know why? The reason is that they have no notions of artificial intelligence. So, future programmers will no longer find work without having knowledge of this particular field that is constantly evolving.