Название: Data and Process Visualisation for Graphic Communication: A Hands-on Approach with Python
Автор: Francesco Bianconi
Издательство: Springer
Год: 2024
Страниц: 242
Язык: английский
Формат: pdf (true)
Размер: 20.1 MB

This book guides the reader through the process of graphic communication with a particular focus on representing data and processes. It considers a variety of common graphic communication scenarios among those that arise most frequently in practical applications. Graphic communication is a form of visual communication that employs images and graphics to convey information, ideas, and messages. It plays a fundamental role in several aspects of our personal and professional lives including education and learning, science and research, brainstorming, and decision-making as well as marketing and branding. This volume aims at guiding the reader through the process of graphic communication with particular focus on representing data and processes. It considers a variety of common graphic communication scenarios among those that arise most frequently in practical applications, e.g., representing magnitudes, proportions, relations, groups, geographical data, timelines, etc. At the time of writing Python is consistently ranked as the most popular programming language in the world. As for data visualization, there are already a number of packages available: Bokeh, HoloViz, Matplotlib, Plotly and Seaborn are just some examples. In writing this book we therefore had to made a choice about which package(s) to consider for the examples presented herein. Then, for each type of chart presented in the book, we proposed the implementation that we thought was the most clear and concise. When there were substantially equivalent solutions, we favored Matplotlib, both due to personal experience and the historical importance of this library.

Название: Introduction to Python: With Applications in Optimization, Image and Video Processing, and Machine Learning
Автор: David Báez-López, David Alfredo Báez Villegas
Издательство: CRC Press
Серия: The Python Series
Год: 2024
Страниц: 453
Язык: английский
Формат: pdf (true), epub
Размер: 11.1 MB

Introduction to Python: with Applications in Optimization, Image and Video Processing, and Machine Learning is intended primarily for advanced undergraduate and graduate students in quantitative sciences such as mathematics, Computer Science, and engineering. In addition to this, the book is written in such a way that it can also serve as a self-contained handbook for professionals working in quantitative fields including finance, IT, and many other industries where programming is a useful or essential tool. The book is written to be accessible and useful to those with no prior experience of Python, but those who are somewhat more adept will also benefit from the more advanced material that comes later in the book. Python is a high-level programming language that supports procedural, imperative, object-oriented, and functional modes. This book covers the first three modes. Python has a simple easy to learn syntax. Python supports modules, libraries, and packages, encouraging program modularity and code reuse. The book may be divided in two parts. The first part, comprised of Chapters 1 to 8, can be used by a person interested in learning Python from scratch; that is, he/she does not have any knowledge of Python. The learning goes from installing Python to implementing functions and generating complex plots. The second part covers advanced topics such as optimization, image and video processing, and Machine Learning using Keras, TensorFlow, and neural networks. Throughout the book, the use of external modules or libraries makes the Python programs very powerful.

Название: Machine Learning for Materials Discovery: Numerical Recipes and Practical Applications
Автор: N. M. Anoop Krishnan, Hariprasad Kodamana, Ravinder Bhattoo
Издательство: Springer
Год: 2024
Страниц: 287
Язык: английский
Формат: pdf (true)
Размер: 11.5 MB

Focusing on the fundamentals of Machine Learning, this book covers broad areas of data-driven modeling, ranging from simple regression to advanced Machine Learning and optimization methods for applications in materials modeling and discovery. The book explains complex mathematical concepts in a lucid manner to ensure that readers from different materials domains are able to use these techniques successfully. A unique feature of this book is its hands-on aspect―each method presented herein is accompanied by a code that implements the method in open-source platforms such as Python. This book is thus aimed at graduate students, researchers, and engineers to enable the use of data-driven methods for understanding and accelerating the discovery of novel materials. We discuss the transformative impact of Deep Learning compared to classical approaches, which heavily rely on handcrafted features and hyperparameter tuning. To this extent, the chapter explores a range of advanced Deep Learning models, including Convolutional Neural Networks (CNNs) for materials image analysis, Long Short-Term Memory networks (LSTMs) for sequential materials data, Generative Adversarial Networks (GANs) for generating new material structures, Graph Neural Networks (GNNs) for analyzing materials graphs, Variational Autoencoders (VAEs) for materials representation learning, and Reinforcement Learning (RL) which has been widely used in materials domain. Each model is presented with a detailed explanation of its underlying principles, architectures, and training methodologies.

Название: Understanding Cryptography: From Established Symmetric and Asymmetric Ciphers to Post-Quantum Algorithms, 2nd Edition
Автор: Christof Paar, Jan Pelzl, Tim Güneysu
Издательство: Springer
Год: 2024
Страниц: 555
Язык: английский
Формат: pdf (true)
Размер: 11.4 MB

Understanding and employing cryptography has become central for securing virtually any digital application, whether user app, cloud service, or even medical implant. Heavily revised and updated, the long-awaited second edition of Understanding Cryptography follows the unique approach of making modern cryptography accessible to a broad audience, requiring only a minimum of prior knowledge. After introducing basic cryptography concepts, this seminal textbook covers nearly all symmetric, asymmetric, and post-quantum cryptographic algorithms currently in use in applications—ranging from cloud computing and smart phones all the way to industrial systems, block chains, and cryptocurrencies. The book has many features that make it a unique source for students, practitioners and researchers. We focus on practical relevance by introducing the majority of cryptographic algorithms that are used in modern real-world applications. With respect to symmetric algorithms, we introduce the block ciphers AES, DES and triple-DES as well as PRESENT, which is an important example of a lightweight cipher. We also describe three popular stream ciphers. Regarding asymmetric cryptography, we cover all three public-key families currently in use: RSA, discrete logarithm schemes and elliptic curves.

Название: Многопоточный Python
Автор: Павел Хошев
Издательство: Stepik
Год: 2024
Формат: HTML
Страниц: много
Размер: 460 Mb
Язык: Русский

С этим курсом вы освоите многопоточное программирование и откроете для себя мир высокопроизводительных приложений! Курс предлагает хорошо структурированную теорию, практические задания, поддержку экспертов и доступ к сообществу. Погрузитесь в учебу, примените полученные знания на практике и станьте востребованным специалистом.

Название: Linux Coding & Programming Tricks & Tips - 18th Edition 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Язык: английский
Формат: pdf
Размер: 38.5 MB

Linux Tricks and Tips - это идеальное цифровое руководство для тех читателей, которые желают поднять свои навыки программирования на более высокий уровень. Вы хотите улучшить свой пользовательский опыт или получить инсайдерские знания? Вы хотите учиться непосредственно у экспертов в этой области? Хотите узнать бесчисленные шорткаты, которыми пользуются профессионалы? На страницах этого нового издания для продвинутых пользователей вы узнаете все, что нужно, чтобы стать более уверенным, знающим и опытным пользователем. Пользователем, который получит максимальную отдачу от программирования на Python и C++,а значит,и от самого Linux.

Название: Introduction to Game Programming using Processing: For Designers, Artists, Players, Non-Tech People and Everybody Else
Автор: Daniel Cermak-Sassenrath
Издательство: CRC Press
Год: 2024
Страниц: 349
Язык: английский
Формат: pdf (true)
Размер: 11.3 MB

This is an introductory textbook focusing on games (specifically interaction and graphics) as a pathway into programming. It empowers its readers to do basic programming, prototyping, creating games and other highly interactive applications, all from scratch and without any prior programming knowledge. Using the popular programming language Processing, it describes, explains, and demonstrates the basic and general programming principles and mechanisms used in typical game algorithms and concrete game projects. Chapters cover basic graphics, text output, loops, data types and variables, movement, time, audio and sound, debugging, classes and objects, event-based programming, real-time input controls, computer speed compensation, animation, tiling, scrolling, collision detection, basic AI and much more. Additional support materials such as code examples and demo programs are available to download from the book’s webpage. This book is an attempt to support non-tech people such as designers, artists, players, other non-tech people and the interested public, to start programming, hopefully, in a fun and accessible way: Games as a pathway into programming. It empowers readers to do basic programming, prototyping, creating games and other highly interactive applications, and to talk competently with tech people. This is also an entry-level introduction to programming with examples in the popular language Processing. Basic and general programming principles and mechanisms are described, explained, demonstrated and applied in typical game algorithms and concrete game projects. It is to be expected that for many years, Processing will continue to play a role in learning programming and as a preferred language for artists and designers.

Название: Introduction to Multidisciplinary Science with Artificial Intelligence: Geodesy, Geotherms, Quantum Entanglement, and Spectroscopy
Автор: Luc Thomas Ikelle
Издательство: CRC Press
Год: 2024
Страниц: 823
Язык: английский
Формат: pdf (true)
Размер: 50.9 MB

With the huge progress being made in the field of Artificial Intelligence (AI), the new jobs are about innovation. Broadly speaking, AI is a set of techniques that are aimed at approximating some aspects of human or animal cognition by inserting computer software into robots and other related systems. AI systems can nowadays perform many traditionally human tasks with high efficiency and without errors. The book is about multidisciplinary science education. The challenges of our time, such as improving the length and quality of lives on Earth and short- and long-distance communication and transportation. In this book, we provide readers with the multidisciplinary education necessary to meet the scientific and technological challenges of our time while optimizing the college experience for students. The fundamental notions addressed in this book include gravitational forces and energy; dark matter and dark energy; heat transfer in solid Earth, stars’ interiors, and human bodies; electromagnetic radiation and spectroscopy; quantum entanglement and computing; accretion disks; matter in plasma state; and exoplanets. We illustrate the importance of these notions with applications across disciplines, including monitoring the deformation of the solid Earth’s surface using satellite measurements, unusual gravity anomalies in Antarctica, a view and characterization of the far side of our Moon, Earth’s climate, Titan’s anti-greenhouse effect, long-distance communication between Earth and the planets and exoplanets, etc. Finally, the book contains analytical and computational problems, including MATLAB software developed especially for the classes associated with this book.

Название: Financial Data Analytics with R: Monte-Carlo Validation
Автор: Jenny K. Chen
Издательство: CRC Press
Год: 2025
Страниц: 298
Язык: английский
Формат: pdf (true)
Размер: 13.7 MB

Financial Data Analysis with R: Monte-Carlo Validation is a comprehensive exploration of statistical methodologies and their applications in finance. Readers are taken on a journey in each chapter through practical explanations and examples, enabling them to develop a solid foundation of these methods in R and their applications in finance. This book aims to serve as a comprehensive guide for students, researchers, and practitioners seeking to harness the power of R for analyzing financial data. The journey begins with a solid foundation in both financial theory and R programming, gradually progressing to more advanced topics such as time series analysis, risk and risk management. The practical examples provided throughout the book are rooted in real-world financial scenarios, offering readers a bridge between academic concepts and practical applications. The book goes beyond just teaching statistical methods in R and incorporates a unique section of informative Monte-Carlo simulations. These Monte-Carlo simulations are uniquely designed to showcase the reader the potential consequences and misleading conclusions that can arise when fundamental model assumptions are violated. Through step-by-step tutorials and realworld cases, readers will learn how and why model assumptions are important to follow. With a focus on practicality, Financial Data Analysis with R: Monte-Carlo Validation equips readers with the skills to construct and validate financial models using R.

Название: Linear Algebra in Data Science
Автор: Peter Zizler, Roberta La Haye
Издательство: Birkhäuser/Springer
Год: 2024
Страниц: 202
Язык: английский
Формат: pdf (true), epub
Размер: 16.3 MB

Data Science is an exciting, emerging research area in the forthcoming digital age. It draws from a multitude of disciplines. We intend to show the reader the fundamental role of linear algebra in Data Science. This book showcases various Data Science topics as seen through the lens of linear algebra. This textbook explores applications of linear algebra in Data Science at an introductory level, showing readers how the two are deeply connected. The authors accomplish this by offering exercises that escalate in complexity, many of which incorporate MATLAB. Practice projects appear as well for students to better understand the real-world applications of the material covered in a standard linear algebra course. Some topics covered include singular value decomposition, convolution, frequency filtering, and neural networks. Linear Algebra in Data Science is suitable as a supplement to a standard linear algebra course. We assume the reader is either familiar with foundational results in linear algebra or willing to consult a linear algebra text of their choice for specific results as they read our text. Readers with the basic linear algebra knowledge and who are interested in Data Science courses will find our text useful. Linear algebra is a pillar for Data Science, and understanding this will enable the student to grasp the procedures and techniques used. It will also provide the student with the ability to go further into the Data Science paradigm.