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 Free Download Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning English | 2025 | ISBN: 1837027870 | 1045 Pages | MOBI AZW3 | 181 MB Mathematics of Machine Learning provides a rigorous yet accessible introduction to the mathematical underpinnings of machine learning, designed for engineers, developers, and data scientists ready to elevate their technical expertise. With this book, you'll explore the core disciplines of linear algebra, calculus, and probability theory essential for mastering advanced machine learning concepts.  Free Download Mathematics for Sustainable Industry English | 2025 | ISBN: 3031859251 | 348 Pages | PDF EPUB (True) | 63 MB This volume gathers selected, peer-reviewed contributions presented at the 5th International Seminar on Mathematics in Industry - ISMI2024, held on September 9-11, 2024 in Kuala Lumpur, Malaysia. Articles in this volume touch on fields such as applied mathematics, applied probability theory and stochastic modeling, statistical modeling, operations research, biomathematics, optimization, inventory management, supply chain, and computational mathematics, all with an emphasis on solutions to real-world problems. Many of the studies contained here closely relate to the United Nations' Sustainable Development Goals, namely SDG 9 (Industry) and SDG 3 (Health), potentially inspiring practitioners and scholars to deploy these findings and pursue similar avenues of research.  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Free Download Mathematical Modeling, Applied Analysis and Computational Methods English | 2025 | ISBN: 9819634598 | 298 Pages | PDF EPUB (True) | 61 MB This volume presents a curated selection of papers presented at the International Conference on Applied and Industrial Mathematics (ICAIM 2023), hosted by Sharda University in Greater Noida, Uttar Pradesh, India, from 24-26 March 2023. It delves into diverse realms of mathematical modelling, applied analyses, computational methods and industrial mathematics. Each chapter within this collection offers intriguing insights into tackling real-world challenges through the lens of mathematical modelling and computational approaches. The book traverses an array of compelling subjects from safeguarding secrets through specialized codes to optimizing solar energy utilization. It illuminates how mathematics is potent in unravelling intricate problems, such as understanding disease propagation or enhancing machine learning algorithms. Through lucid explanations and engaging examples, this volume is tailored for curious minds eager to delve into the marvels of mathematics from fresh perspectives.  Free Download Mathematical Methods For The Natural And Engineering Sciences English | 2017 | ISBN: 981320270X | 640 Pages | PDF (True) | 4 MB This second edition provides a broad range of methods and concepts required for the analysis and solution of equations which arise in the modeling of phenomena in the natural, engineering, and applied mathematical sciences. It may be used productively by both undergraduate and graduate students, as well as others who wish to learn, understand, and apply these techniques. Detailed discussions are also given for several topics that are not usually included in standard textbooks at this level of presentation: qualitative methods for differential equations, dimensionalization and scaling, elements of asymptotics, difference equations and several perturbation procedures. Further, this second edition includes several new topics covering functional equations, the Lambert-W function, nonstandard sets of periodic functions, and the method of dominant balance. Each chapter contains a large number of worked examples and provides references to the appropriate books and literature.  Free Download Math for Data Science English | 2025 | ISBN: 3031897064 | 588 Pages | PDF (True) | 21 MB Math for Data Science presents the mathematical foundations necessary for studying and working in Data Science. The book is suitable for courses in applied mathematics, business analytics, computer science, data science, and engineering. The text covers the portions of linear algebra, calculus, probability, and statistics prerequisite to Data Science. The highlight of the book is the machine learning chapter, where the results of the previous chapters are applied to neural network training and stochastic gradient descent. 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Accordingly, this is a suitable textbook for undergraduate and graduate students in the fields of mechanical engineering, materials science, metallurgical engineering, and related disciplines. The book incorporates two-dimensional materials, crystal defects, mass transport, thermodynamics of phase, solidification heat transfer, solidification and phase diagrams related to nucleation particle phases and explains solid-state phase transformation, mechanical behaviour and fracture toughness, non-destructive methods, physical and optical properties of solids, and electrochemical corrosion. It also stands as an excellent reference treatise for practicing and consulting engineers. Moreover, the book is appropriate for graduate-level coursework, covering advanced subjects including quantum mechanics, two dimensional materials, fracture mechanics, non-destructive methods for evaluating structural integrity, and advanced analytical techniques in some appendices.  Free Download Materials Science And Engineering English | 2017 | ISBN: 9813226501 | 1168 Pages | PDF (True) | 271 MB In this conference, we have received over 272 high-quality papers, however, only 160 articles are included in the proceedings, covering topics such as ceramics and glasses, amorphous materials, nanomaterials and thin layers, soft magnetic materials, biomaterials, polymers, photovoltaic materials, steels, tool materials, composites, as well as functional and smart materials. |
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