Artificial Intelligence for Big Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence for Big Data write by Anand Deshpande. This book was released on 2018-05-22. Artificial Intelligence for Big Data available in PDF, EPUB and Kindle. Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.
AI and Big Data’s Potential for Disruptive Innovation
AI and Big Data’s Potential for Disruptive Innovation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook AI and Big Data’s Potential for Disruptive Innovation write by Strydom, Moses. This book was released on 2019-09-27. AI and Big Data’s Potential for Disruptive Innovation available in PDF, EPUB and Kindle. Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.
Big Data, Big Design
Big Data, Big Design - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Big Data, Big Design write by Helen Armstrong. This book was released on 2021-11-04. Big Data, Big Design available in PDF, EPUB and Kindle. Big Data, Big Design provides designers with the tools they need to harness the potential of machine learning and put it to use for good through thoughtful, human-centered, intentional design. Enter the world of Machine Learning (ML) and Artificial Intelligence (AI) through a design lens in this thoughtful handbook of practical skills, technical knowledge, interviews, essays, and theory, written specifically for designers. Gain an understanding of the design opportunities and design biases that arise when using predictive algorithms. Learn how to place design principles and cultural context at the heart of AI and ML through real-life case studies and examples. This portable, accessible guide will give beginners and more advanced AI and ML users the confidence to make reasoned, thoughtful decisions when implementing ML design solutions.
Transforming Healthcare with Big Data and AI
Transforming Healthcare with Big Data and AI - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Transforming Healthcare with Big Data and AI write by Mingbo Gong. This book was released on 2020-04-01. Transforming Healthcare with Big Data and AI available in PDF, EPUB and Kindle. 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.
HPC, Big Data, and AI Convergence Towards Exascale
HPC, Big Data, and AI Convergence Towards Exascale - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook HPC, Big Data, and AI Convergence Towards Exascale write by Olivier Terzo. This book was released on 2022-01-13. HPC, Big Data, and AI Convergence Towards Exascale available in PDF, EPUB and Kindle. HPC, Big Data, AI Convergence Towards Exascale provides an updated vision on the most advanced computing, storage, and interconnection technologies, that are at basis of convergence among the HPC, Cloud, Big Data, and artificial intelligence (AI) domains. Through the presentation of the solutions devised within recently founded H2020 European projects, this book provides an insight on challenges faced by integrating such technologies and in achieving performance and energy efficiency targets towards the exascale level. Emphasis is given to innovative ways of provisioning and managing resources, as well as monitoring their usage. Industrial and scientific use cases give to the reader practical examples of the needs for a cross-domain convergence. All the chapters in this book pave the road to new generation of technologies, support their development and, in addition, verify them on real-world problems. The readers will find this book useful because it provides an overview of currently available technologies that fit with the concept of unified Cloud-HPC-Big Data-AI applications and presents examples of their actual use in scientific and industrial applications.
