Showing results for "Big data" in Engineering

Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.

In our age of accelerating progress in so many fields, it’s easy to lose sight of the underlying innovation that makes the data analytics revolution possible. These 24 lectures introduce you to the key concepts, methods, and accomplishments of this versatile approach to problem solving. You need no expertise in mathematics to follow this exciting story. Tim Chartier, professor of mathematics and computer science, explains the basic computational techniques used in data analytics, but his focus is on how these ideas are applied and the amazing results they achieve.

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.

Do you want to discover all the secrets of Big Data, Deep Learning, and everything in between? Have you ever asked yourself how can artificial intelligences learn from us? Do you want understand how does your smartphone personal assistant can understand you? In this guide, Artus Duval will show you everything you need to know about big data, machine learning, artificial intelligence, and its huge impact on our world; a swell as how to benefit from it 100 percent!

In this book, Michael Smith and Rahul Telang, experts on entertainment analytics, show how the success of House of Cards upended the film and TV industries - and how companies like Amazon and Apple are changing the rules in other entertainment industries, notably publishing and music. We're living through a period of unprecedented technological disruption in the entertainment industries.

A man shoots down a drone that is flying over his private property. A retail store uses predictive data analytics to send pregnancy-related advertising to a teenager who has not told her parents about her condition. A police officer places a GPS device on a suspected criminal's car to follow him and build a case against him. The news is full of such stories, in which new technologies lead to dilemmas that could not have been imagined just a few decades ago.

Big Data Revolution is a guide to improving performance, making better decisions, and transforming business through the effective use of big data. Listeners are guided through tried-and-true methodologies for getting more out of data and using it to the utmost advantage. This audiobook describes the major trends emerging in the field, the pitfalls and triumphs being experienced, and the many considerations surrounding big data, all while guiding listeners toward better decision-making from the perspective of a data scientist.

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.

Innovation influences the market and its operators, especially about competition conditions. One of the most significant technological advances relates to the possibility of capturing a huge amount of information and processing them rapidly: two of the main features that make up the phenomenon known as big data. This not only entails the emergence of specialized operators in these activities, but also makes a "data economy" possible.

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.

Explosion of the economic relevance of data is related to: first, technological progress that has drastically reduced the costs of collecting and storing data; second, the advances in analytic techniques that have allowed for more advanced processing to extract greater value from available data. So, more value is extracted from exhausted data. Information generated for one purpose can and should be reused for another one, which means that data moves from primary to secondary uses. Data are more valuable over time.

If you are a budding analyst or want to freshen up on your concepts, this book is for you. It has all the basic information you need to help you become a data analyst or scientist.

Les parents favorisent-ils les garçons plutôt que les filles ? L'école que l'on fréquente influence-t-elle réellement notre réussite ? Mentons-nous souvent sur notre sexualité ? En ce début de XXIe siècle, nos navigations Internet génèrent huit millions de giga-octets de données chaque jour. Une quantité stupéfiante d'informations qui en disent long sur chacun d'entre nous, car c'est à notre moteur de recherche que nous confions nos questions et nos pensées les plus intimes.

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.

Forget Excel sheets and static bar graphs and charts - there are more innovative ways that you can capture data, make sense of it, present it to your colleagues, and take the necessary action to provide value for your business. With today's fast-paced world and cutthroat competition, your organization may fall behind if you fail to make use of the emerging trend of big data and data analytics. Whether you want to understand client behaviors, reduce processing time in your factory, or integrate information from several branches, this book can become your guide.