Machine Learning and Artificial Intelligence for Agricultural Economics: Prognostic Data Analytics to Serve Small Scale Farmers Worldwide, Vuppalapati Chandrasekar
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.
Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics ISBN: 179981193X ISBN-13(EAN): 9781799811930 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 27027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics ISBN: 1799811921 ISBN-13(EAN): 9781799811923 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 35897.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Описание: This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.
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 maximise YOUR business.
Yes, you have customers that love your product. However, you're having trouble finding new customers and captivating their attention. You realized you're also losing customers, and you have no clue what you can do to prevent this from happening. How do I stand out in a crowd of businesses? How do I target my perfect client and make them choose ME? If this sounds like you, Data Analytics for Businesses if the guide you need.
This book will walk you through the fundamental principles of data science and how to apply the "data analytic mindset" when approaching your business. You will learn how to extract valuable insights from data sources you ALREADY HAVE, and make informed business decisions to help you achieve your goals.
With real-world examples of how to apply data analytics to your business, this book does what others fail to do. Break the process down step by step, so you can optimize unique parts of your business; such as improving customer loyalty or reducing churn. This guide also helps you understand the many data-mining techniques in use today.
Discover the value of applied data science for business decision-making. You'll learn how to think data-analytically, and make connections between data sources to unveil insights you've never imagined. In this book you will learn:
✔︎ Why every company should be leveraging Data Analytics ✔︎ The difference between Big Data, Data Science and Data Analytics. ✔︎ How to achieve your goals by applying data-analytical thinking to your business ✔︎ The recommended data mining techniques for each of your business goals. ✔︎ The most important thing to remember when extracting knowledge from your data. ✔︎ How to use data analytics to improve brand loyalty and customer experience. ✔︎ How to hire the best data scientist, and more.
If you are overwhelmed by this whole new topic of data analytics, don't be. This guide is designed for beginners, with all the guidance you need to understand the fundamentals of harnessing data analytics for your business. So even if you have never heard about data analytics until today, I promise we will walk through this step- by-step.
By the end of this, you'll be able to think analytically and make informed business decisions. This book illustrates how EASY it is to find success by just applying a few principles.
So stop reading this description, and start reading Data Analytics for Businesses instead. Scroll up, and CLICK BUY now
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.
Автор: Li, Fanzhang / Zhang, Li / Zhang, Zhao Название: Dynamic Fuzzy Machine Learning ISBN: 3110518708 ISBN-13(EAN): 9783110518702 Издательство: Walter de Gruyter Рейтинг: Цена: 22439.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.
Описание: A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data.
ГўВВђ 55% OFF for Bookstores! NOW at $11.99 instead of $24.99! Your Customers Will Never Stop Using This Awesome Book!
Автор: Rik Das, Siddhartha Bhattacharyya, Sudarshan Nandy Название: Machine Learning Applications: Emerging Trends ISBN: 3110608537 ISBN-13(EAN): 9783110608533 Издательство: Walter de Gruyter Цена: 18586.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
