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Soviet Literature
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Predicting Crop Phenology
Predicting Crop Phenology focuses on an analysis of the issues faced in predicting the phenology of crop plants and weeds. It discusses how these issues have been handled by active crop growth simulation model developers and emphasizes areas such as the role of modeling in agricultural research and the roles of temperature, length of day, and water stress in plant growth. This comprehensive text also discusses modeling philosophy and programming techniques in modeling crop development and growth. It presents up-to-date information on phenology models for wheat, maize, sorghum, rice, cotton, and several weed species. Predicting Crop Phenology reviews important data for agricultural engineers, plant physiologists, agricultural consultants, researchers, extension agents, model developers, agricultural science instructors and students.
Deep Learning Interviews
The book's contents is a large inventory of numerous topics relevant to DL job interviews and graduate level exams. That places this work at the forefront of the growing trend in science to teach a core set of practical mathematical and computational skills. It is widely accepted that the training of every computer scientist must include the fundamental theorems of ML, and AI appears in the curriculum of nearly every university. This volume is designed as an excellent reference for graduates of such programs.
Oxford Textbook of Epilepsy and Epileptic Seizures
Part of the Oxford Textbooks in Clinical Neurology (OTCN) series, this volume covers the scientific basis, clinical diagnosis, and treatment of epilepsy and epileptic seizures, and is complemented by an online edition.
