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Resources in mathematics, computer science, and other natural sciences; many use the Maple computer language. Text in English and Russian.

Computer science --- Mathematics

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Data Analysis in Molecular Biology and Evolution introduces biologists to DAMBE, a proprietary, user-friendly computer program for molecular data analysis. The unique combination of this book and software will allow biologists not only to understand the rationale behind a variety of computational tools in molecular biology and evolution, but also to gain instant access to these tools for use in their laboratories. Data Analysis in Molecular Biology and Evolution serves as an excellent resource for advanced level undergraduates or graduates as well as for professionals working in the field.

Life sciences. --- Computer science. --- Data structures (Computer science). --- Biochemistry. --- Evolutionary biology. --- Animal anatomy. --- Life Sciences. --- Animal Anatomy / Morphology / Histology. --- Computer Science, general. --- Evolutionary Biology. --- Data Structures. --- Biochemistry, general. --- Morphology (Animals). --- Evolution (Biology). --- Data structures (Computer scienc. --- Data structures (Computer science) --- Biological chemistry --- Chemical composition of organisms --- Organisms --- Physiological chemistry --- Biology --- Chemistry --- Medical sciences --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Animal evolution --- Animals --- Biological evolution --- Darwinism --- Evolutionary biology --- Evolutionary science --- Origin of species --- Evolution --- Biological fitness --- Homoplasy --- Natural selection --- Phylogeny --- Informatics --- Science --- Animal anatomy --- Physiology --- Composition --- Anatomy --- Molecular biology --- Evolution (Biology) --- Data processing

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Cet ouvrage détaille comment écrire ou enrichir des articles dans les wikis, systèmes de gestion de contenu libres d'accès aux visiteurs reconnus. Plusieurs chapitres sont consacrés à l'activité des administrateurs système et de site.

Wikis (Computer science) --- Web services --- Wikis (Informatique) --- Services Web --- Handbooks, manuals, etc. --- Guides, manuels, etc.

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Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume.

Machine learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Seismology --- Geology --- Neural networks (Computer science) --- Machine learning --- Data processing --- Technological innovations

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Vertebrates --- Classification --- Animal remains (Archaeology) --- -Animal remains (Archaeology) --- -Archaeozoology --- Zooarchaeology --- Zoology in archaeology --- Archaeology --- Bones --- Animal paleopathology --- Data bases --- Computer programs --- Databases --- Methodology --- -Data bases --- Archaeozoology --- Informatique --- Computer science --- Vertebres --- Zoologie