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CC CHATTERJEE’S HUMAN PHYSIOLOGY, VOLUME 1
Completely revised, entirely rewritten, thoroughly updated, and judiciously enlarged by a highly qualified and experienced team of editors.
Aetcom
The manual is especially designed to cover the competencies recommended by Medical Council of India for the first professional MBBS students. It has been written by highly experienced, dynamic and devoted medical academicians and clinicians who are well versed with the latest trends in medical education, training and clinical practice.
The Billionaire’s Apprentice
'‘A page-turning cops and robbers story set against the backdrops of Silicon Valley and Wall Street.’ – Adam Lashinsky, bestselling author of Inside Apple: How America's Most Admired-and Secretive-Company Really Works
Islamic Law of the Sea
This pioneering research brings into focus the Islamic contribution and influence in the development of the modern law of the sea.
An Aging World
Provides statistical information on the worldwide population of people 65 years old or older.
Singapore in Global History
This important overview explores the connections between Singapore's past with historical developments worldwide until present day. The contributors analyse Singapore as a city-state seeking to provide an interdisciplinary perspective to the study of the global dimensions contributing to Singapore's growth. The book's global perspective demonstrates that many of the discussions of Singapore as a city-state have relevance and implications beyond Singapore to include Southeast Asia and the world. This vital volume should not be missed by economists, as well as those interested in imperial histor.
Likewar
Social media has been weaponized, as state hackers and rogue terrorists have seized upon Twitter and Facebook to create chaos and destruction. This urgent report is required reading, from defense experts P.W. Singer and Emerson T. Brooking.
Large-scale Kernel Machines
Solutions for learning from large scale datasets, including kernel learning algorithms that scale linearly with the volume of the data and experiments carried out on realistically large datasets. Pervasive and networked computers have dramatically reduced the cost of collecting and distributing large datasets. In this context, machine learning algorithms that scale poorly could simply become irrelevant. We need learning algorithms that scale linearly with the volume of the data while maintaining enough statistical efficiency to outperform algorithms that simply process a random subset of the data. This volume offers researchers and engineers practical solutions for learning from large scale ...
