Pradeep Singh, Balasubramanian Raman | Python for Mathematical Thinking (2026) [PDF, EPUB]
Автор: Pradeep Singh, Balasubramanian Raman
Издательство: Springer
ISBN: 978-9819540792
Жанр: Python Programming, Computer Programming Languages, Engineering
Язык: Английский
Формат: PDF, EPUB
Качество: Изначально электронное (ebook)
Иллюстрации: Цветные и черно-белые
Описание:This book offers a rigorous yet approachable pathway to applying Python for mathematical problem-solving, spanning foundational concepts to advanced theoretical frameworks. It bridges the gap between abstract mathematics and computational execution, guiding readers through a logically structured, step-by-step journey. Emphasizing mathematical reasoning, symbolic computation, and real-world problem modeling, it equips readers to analyze, simulate, and visualize complex structures with clarity and efficiency. Ideal for students, researchers, and professionals in Mathematics, Data Science, AI, Physics, and Computational Science, it cultivates both programming skill and deep mathematical intuition.
Chapter 1: Introduction.
Chapter 2: Mathematical Foundations: Translates core university-level arithmetic, algebra, and inequalities into code.
Chapter 3: Calculus with Python: Covers symbolic differentiation/integration (SymPy) and numerical methods.
Chapter 4: Data Structures & Algorithms: Covers complexity, search, sorting, and graph algorithms (BFS/DFS).
Chapter 5: Probability & Statistics: Addresses random variables, distributions, and inferential statistics.
Chapter 6: Differential Equations: Covers analytical and numerical solvers (Runge–Kutta, Finite Element) for various equation types.
Chapter 7: Discrete Mathematics: Explores sets, logic, and combinatorics using itertools and networkx.
Chapter 8: Numerical Methods: Details root-finding, interpolation, and matrix factorization.
Chapter 9: Chaos & Dynamical Systems: Covers complex systems analysis, bifurcation, and forecasting.
Chapter 10: Data Science & ML: Covers feature engineering, regression, and neural networks.
Chapter 11: Advanced Topics: Explores Fourier/wavelet analysis and quantum computing basics
Скриншоты:
Время раздачи: с 10 до 20 (минимум до появления первых 3-5 скачавших) 
