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réf. 9819536677.Gpaperback. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book. paperback
réf. 9819656389.Gpaperback. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book. paperback
2026réf. __9819536677Springer-Nature New York Inc 2026. Paperback. New. pap/psc edition. 330 pages. 9.25x6.10x9.17 inches. Springer-Nature New York Inc paperback
2025réf. x-9819656389Springer-Nature New York Inc 2025. Paperback. New. 440 pages. 9.26x6.11x9.21 inches. Springer-Nature New York Inc paperback
réf. 50236201like new. unknown
réf. 50236201-nnew. unknown
réf. 51431835like new. unknown
réf. 51431835-nnew. unknown
réf. A9789819536672Paperback / softback. New. This textbook serves as a companion to "A Mathematical Introduction to Data Science". It uses Python programming to provide a comprehensive foundation in the mathematics needed for data science. It is designed for anyone with a basic mathematical background including students and self-learners interested in understanding the principles behind the computational algorithms used in data science. The focus of this book is to demonstrate how programming can aid in this understanding and be used in solving mathematical problems. It is written using Python as its programming language but readers do not need prior knowledge of Python to benefit from it. Some examples from "A Mathematical Introduction to Data Science" are used to illustrate key concepts such as sets functions linear algebra calculus and probability and statistics through Python programming though it is not necessary to have seen the examples before. Further this textbook shows how those mathematical concepts can be applied in widely used computational algorithms such as Principal Component Analysis Singular Value Decomposition Linear Regression in two and more dimensions Simple Neural Networks Maximum Likelihood Estimation Logistic Regression and Ridge Regression. This textbook is designed with the assumption that readers have no prior knowledge of Python but possess a basic understanding of programming concepts such as control flow. Ideally readers should have both this book and its companion "A Mathematical Introduction to Data Science". However those with a strong mathematical background and an interest in programming implementations can benefit from reading this textbook alone. paperback
réf. A9789819656387Paperback / softback. New. This textbook provides a comprehensive foundation in the mathematics needed for data science for students and self-learners with a basic mathematical background who are interested in the principles behind computational algorithms in data science. paperback
réf. ria9789819656387_inpPaperback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; This textbook provides a comprehensive foundation in the mathematics needed for data science for students and self-learners with a basic mathematical background who are interested in the principles behind computational algorithms in dat paperback
réf. B9789819656387Paperback / softback. New. This textbook provides a comprehensive foundation in the mathematics needed for data science for students and self-learners with a basic mathematical background who are interested in the principles behind computational algorithms in data science. paperback
1965réf. 2090502113702237Not Available 1965. Soft Cover. Fine. The book is in fine condition. Not Available paperback
réf. ria9783836429054_inpPaperback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; Organizational learning is widely accepted as a means of sustaining competitive advantage especially for organizations facing discontinuity in the external environment. However in attempting to develop a learning organization many re paperback
réf. B9783836429054Paperback / softback. New. paperback
réf. 3639418832.Gpaperback. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book. paperback
réf. 3836429055.Gpaperback. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book. paperback
2025réf. x-9819684870Springer Nature 2025. Hardcover. New. 500 pages. 9.26x6.11x9.21 inches. Springer Nature hardcover
réf. 51233748like new. unknown
réf. 51233748-nnew. unknown
réf. ria9789819684878_inpHardcover. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; This book aims to illustrate and explain the “Cognitive Metaphorology” from experiential and cultural perspectives and highlights two prominent features of cognitive metaphor: multidimensionality and cross-sphere application hardcover
réf. 0398051895.Ghardcover. Good. Access codes and supplements are not guaranteed with used items. May be an ex-library book. hardcover
réf. 20319366-nnew. unknown
réf. REDR7VSMJY3DW W Norton & Co Inc. spiral_bound. Good. in x in x in. W W Norton & Co Inc unknown
réf. VB2940318588W. W. Norton & Company 2017-06-15. spiral_bound. Very Good. 9x1x10. W. W. Norton & Company unknown
