Tao Wu – författare

Presents a combined view of content and wireless technologies useful to both the industry and academiaOffers a good mix of theory and practice to understand the internal working of the wireless/mobile content delivery networksBridges the gap between the wireless and content research communitiesFocuses not only on the latest technology enablers for speedier content delivery in the mobile Internet, but also on how to integrate them to provide workable end-to-end solutions

Presents a combined view of content and wireless technologies useful to both the industry and academia Offers a good mix of theory and practice to understand the internal working of the wireless/mobile content delivery networks Bridges the gap between the wireless and content research communities Focuses not only on the latest technology enablers for speedier content delivery in the mobile Internet, but also on how to integrate them to provide workable end-to-end solutions

This book is the scientific summary of the authors fifty years of experience in tumor surgery and more than twenty years of cancer research results and clinical validation. The book is divided into three sections and fifteen chapters. The first chapter, Pathfinder, starts from the beginning of the experimental study, which introduced how to explore the etiology and pathogenesis of cancer and learned the new revelation from these and had the new discoveries and new knowledge. In section or chapter 2, Footprint, the author had the multi-angle analysis and comments about the traditional cancer therapy and proposed the suggestion of the cancer treatment, as well as innovative results generated through laboratory research and clinical validation, including cancer initiation and metastasis, a new method of cancer treatment, both of which traditional radical surgery and radiotherapy and chemotherapy case review and reflection, and the experimental results and typical cases of clinical data of the applications of XZ-C anti-cancer immune regulation drug treatment of malignant tumors. In the foreword, the author mainly gives the suggestions and the general strategy of attacking the cancer. In this book, the contents are initiative, the ideas are new, the theories are combined with practice and ideas, theory with practice, has a strong academic value and clinical practicality, is suitable for hospitals at all levels of oncology, cancer specialist clinic doctors, cancer researchers, cancer patients, and their familys reading reference.

This book starts from the classic recommendation algorithms, introduces readers to the basic principles and main concepts of the traditional algorithms, and analyzes their advantages and limitations. Then, it addresses the fundamentals of deep learning, focusing on the deep-learning-based technology used, and analyzes problems arising in the theory and practice of recommender systems, helping readers gain a deeper understanding of the cutting-edge technology used in these systems. Lastly, it shares practical experience with Microsoft 's open source project Microsoft Recommenders. Readers can learn the design principles of recommendation algorithms using the source code provided in this book, allowing them to quickly build accurate and efficient recommender systems from scratch.