000			02358nam a22001937a 4500
999			_c4498 _d4498
005			20230117110640.0
008			230117b ||||| |||| 00| 0 eng d
020			_a9780367895617
082			_a001.422028563 _bLIE
245			_aData analytics and AI
260			_bCRC Press _aBoco Raton _c2021
300			_axxiii, 242 p.
365			_aGBP _b52.99
520			_aAnalytics and artificial intelligence (AI), what are they good for? The bandwagon keeps answering, absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history, within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that "artificial intelligence is included." We are indeed living in exciting times. The question we need to ask is, do we really know how to get business value from these exciting tools? Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data.
650			_aStatistics--Data processing _91492
650			_aArtificial intelligence _91478
700			_aLiebowitz, Jay _910501
942			_2ddc _cBK