Machine Learning and Artificial Intelligence in Marketing and Sales: Essential Reference for Practitioners and Data Scientists, Niladri Syam, Rajeeve Kaul
Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Описание: ★This book includes 2 Manuscripts★Are you looking for new ways to grow your business, with resources you already have? Do you want to know how the big players like Netflix, Amazon, or Shopify use data analytics to MULTIPLY their growth? Keep listening to learn how to use data analytics to maximize YOUR business.
Автор: Saifullah Khalid Название: Applications of Artificial Intelligence in Electrical Engineering ISBN: 1799827186 ISBN-13(EAN): 9781799827184 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 42451.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Artificial intelligence is increasingly finding its way into industrial and manufacturing contexts. The prevalence of AI in industry from stock market trading to manufacturing makes it easy to forget how complex artificial intelligence has become. Engineering provides various current and prospective applications of these new and complex artificial intelligence technologies.
Applications of Artificial Intelligence in Electrical Engineering is a critical research book that examines the advancing developments in artificial intelligence with a focus on theory and research and their implications. Highlighting a wide range of topics such as evolutionary computing, image processing, and swarm intelligence, this book is essential for engineers, manufacturers, technology developers, IT specialists, managers, academicians, researchers, computer scientists, and students.
Автор: Pablo Duboue Название: The Art of Feature Engineering: Essentials for Machine Learning ISBN: 1108709389 ISBN-13(EAN): 9781108709385 Издательство: Cambridge Academ Рейтинг: Цена: 6970.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies.
Описание: So, what is the deal with intelligent machines? Will they soon decide on things such as copyright infringement? How about self-driving trucks and cars?What kind of impact will smart machines have on society and the future of human jobs?
Описание: Cambridge for DGB 2nd Edition is a four-level American English integrated skills series for the Upper Secondary public school market in Mexico. Its syllabus is strictly aligned to the national Direccion General del Bachillerato program. It is a series that offers teachers a hands-on and practical solution to teaching English in the classroom. It builds students` language skills from A1 to A2+ in the CEFR.
Описание: Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.
Описание: The aim of this book is to handle different application problems of science and engineering using expert Artificial Neural Network (ANN). As such, the book starts with basics of ANN along with different mathematical preliminaries with respect to algebraic equations. Then it addresses ANN based methods for solving different algebraic equations viz. polynomial equations, diophantine equations, transcendental equations, system of linear and nonlinear equations, eigenvalue problems etc. which are the basic equations to handle the application problems mentioned in the content of the book. Although there exist various methods to handle these problems, but sometimes those may be problem dependent and may fail to give a converge solution with particular discretization. Accordingly, ANN based methods have been addressed here to solve these problems. Detail ANN architecture with step by step procedure and algorithm have been included. Different example problems are solved with respect to various application and mathematical problems. Convergence plots and/or convergence tables of the solutions are depicted to show the efficacy of these methods. It is worth mentioning that various application problems viz. Bakery problem, Power electronics applications, Pole placement, Electrical Network Analysis, Structural engineering problem etc. have been solved using the ANN based methods.
Автор: Alex Lui, Anna Farzinder, Mingboo Gong Название: Transforming Healthcare with Big Data and AI ISBN: 1641138971 ISBN-13(EAN): 9781641138970 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field.
This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.
Описание: Do you want to learn how ML and AI can be applied in practice and be compatible with human behavior in modern times? If yes, then keep reading...
Machine learning (ML) is a data-driven approach. Hence it implies the availability of large datasets in order to make accurate decisions. In case only a limited dataset is available to solve a particular problem, it is best to use a deterministic approach. When a limited dataset is available it is hard to train a machine learning model and generalize its applicability to other similar problems. The developed model, in this case, is only applicable for the few data it was trained on.
Because ML methods rely solely only on data and the human expertise or judgment is not taken in consideration, it is the data that dictate if the machine learning method will fail or succeed to perform the task it was designed for. The way a machine learning approach works is that a modeler develops a learning algorithm. Then the modeler feeds the learning algorithm with the data and information.
The algorithm learns by itself from the data with no guidance or human interference. It is the algorithm that builds the system. If the data provided for the algorithm is of poor quality and biased then the system is also of poor quality and biased. Hence, cleaning and acquiring the right data to solve a problem with ML problem is very crucial. If the data are biased and noisy it is better to stick with a traditional method. Otherwise, the machine learning method will memorize the noise and provide inaccurate results.
Could Turning Important Decisions over to AI help Humanity? Some might say that's a terrible idea, but how much worse is it today where we've turned over our societies and civilizations to corrupt leadership, crony capitalism, or had to deal with rogue nation-states in other parts of the world with two-bit dictators, religious fanaticism, or the quest to destroy another group of peoples' civilization? Perhaps it's time we came up with a special think tank that could go through all the issues concerning our fears, and what we hope to expect from AI decision-making machines. That is to say how to get the best possible answer, all the time with the greatest probability.
We all watched IBM's "Watson" supercomputer as it won against the top human Jeopardy players. It did pretty well, most all the time; didn't it? Yes, but it wasn't perfect, and perhaps that's the scary part. In fact, some of the mistakes that it did make were mistakes that even a child wouldn't have missed. Still, if there is a group of humans or a think tank, focus group, or Board of Directors constantly surveying the answers and asking additional questions, then perhaps you don't have to worry about an erroneous answer now and again. In fact, it might make you smile and feel good to be a human at that point.
ML is useful anywhere you need to recognize patterns and predict behavior based on historical data. Recognizing patterns could mean anything from character recognition to predictive maintenance to recommending products to customers based on past purchases.
This book gives a comprehensive guide on the following:
Correlation Between ML and Artificial Learning
The Era of Evolution
ML and AI in Practice
Self-Driving Cars
Robots and How they will Change Our Lives
ML, AI and IoT
Ethics of AI
AI and Privacy
Is Artificial Intelligence Dangerous?
Will Humans and Artificial Intelligence Live Together in the Future?
Описание: This book explores the complex ways in which algorithms and big data are reshaping everyday culture, while at the same time perpetuating inequality and intersectional discrimination. It situates issues of humanity, identity, and culture in relation to free will, surveillance, capitalism, neoliberalism, consumerism, solipsism, and creativity.
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