Название: High-Order Models in Semantic Image Segmentation
Автор: Ismail Ben Ayed
Издательство: Academic Press/Elsevier
Год: 2023
Страниц: 250
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

High-Order Models in Semantic Image Segmentation reviews recent developments in optimization-based methods for image segmentation, presenting several geometric and mathematical models that underlie a broad class of recent segmentation techniques. Focusing on impactful algorithms in the Computer Vision community in the last 10 years, the book includes sections on graph-theoretic and continuous relaxation techniques, which can compute globally optimal solutions for many problems. The book provides a practical and accessible introduction to these state-of-the-art segmentation techniques that is ideal for academics, industry researchers, and graduate students in Computer Vision, Machine Learning and medical imaging.

Название: A Beginner's Guide to Introduce Artificial Intelligence in Teaching and Learning
Автор: Muralidhar Kurni, Mujeeb Shaik Mohammed, Srinivasa K.G.
Издательство: Springer
Год: 2023
Страниц: 236
Язык: английский
Формат: pdf (true), epub
Размер: 12.2 MB

This book reimagines education in today’s Artificial Intelligence (AI) world and the Fourth Industrial Revolution. Artificial intelligence will drastically affect every industry and sector, and education is no exception. This book aims at how AI may impact the teaching and learning process in education. This book is designed to demystify AI for teachers and learners. This book will help improve education and support institutions in the phenomena of the emergence of AI in teaching and learning. This book presents a comprehensive study of how AI improves teaching and learning, from AI-based learning platforms to AI-assisted proctored examinations. What Is Artificial Intelligence? Artificial Intelligence, or AI, is the study of using data in large quantities to program intelligent machines. Incorporating previous knowledge and experience, these systems can mimic human performance. It improves how quickly, accurately, and successfully humans can complete tasks. In order to create autonomous devices, AI researchers and developers employ elaborate algorithms and techniques. The foundations of AI are the techniques of Machine Learning and Deep Learning.

Название: README. Суровые реалии разработчиков
Автор: Крис Риккомини, Дмитрий Рябой
Издательство: Питер
Год: 2023
Страниц: 304
Язык: русский
Формат: pdf
Размер: 10.6 MB

Начинающим программистам требуется нечто большее, чем навыки программирования. Столкнувшись с реальной работой, вы моментально понимаете, что самым нужным вещам, имеющим критическое значение для карьеры, не обучают ни в университетах, ни на курсах. Книга «Readme. Суровые реалии разработчиков» призвана восполнить этот пробел. Познакомьтесь с важнейшими практиками инжиниринга, которым обучают разработчиков в ведущих компаниях. В издании описаны современные методы создания, тестирования и эксплуатации программного обеспечения, а также нормы поведения и подходы, повышающие эффективность командной работы. Мы дадим вам практические советы о том, как получать помощь, писать проектную документацию, работать со старым кодом, поддерживать связь во время дежурств, планировать свою нагрузку и взаимодействовать с руководством и остальной командой. Темы достаточно сложные, поэтому в конце каждой главы вы найдете раздел «Повышение уровня» с рекомендуемыми источниками для получения дополнительной информации.

Название: Neural Networks and Deep Learning: A Textbook, 2nd Edition
Автор: Charu C. Aggarwal
Издательство: Springer
Год: 2023
Страниц: 541
Язык: английский
Формат: pdf (true), epub
Размер: 46.8 MB

Neural networks were developed to simulate the human nervous system for Machine Learning tasks by treating the computational units in a learning model in a manner similar to human neurons. Neural networks were developed soon after the advent of computers in the fifties and sixties. Rosenblatt’s perceptron algorithm was seen as a fundamental cornerstone of neural networks, which caused an initial period of euphoria — it was soon followed by disappointment as the initial successes were somewhat limited. Eventually, at the turn of the century, greater data availability and increasing computational power lead to increased successes of neural networks, and this area was reborn under the new label of “Deep Learning.” Although we are still far from the day that Artificial Intelligence (AI) is close to human performance, there are specific domains like image recognition, self-driving cars, and game playing, where AI has matched or exceeded human performance. It is also hard to predict what AI might be able to do in the future. For example, few computer vision experts would have thought two decades ago that any automated system could ever perform an intuitive task like categorizing an image more accurately than a human.

Название: Amazon Stock Price: Visualization, Forecasting, and Prediction Using Machine Learning with Python GUI, Second Edition
Автор: Vivian Siahaan, Rismon Hasiholan Sianipar
Издательство: Balige Publishing
Год: 2023
Страниц: 355
Язык: английский
Формат: epub
Размер: 21.0 MB

The Machine Learning models used predict Amazon stock daily returns as target variable are K-Nearest Neighbor classifier, Random Forest classifier, Naive Bayes classifier, Logistic Regression classifier, Decision Tree classifier, Support Vector Machine classifier, LGBM classifier, Gradient Boosting classifier, XGB classifier, MLP classifier, and Extra Trees classifier. Finally, you will develop GUI to plot boundary decision, distribution of features, feature importance, predicted values versus true values, confusion matrix, learning curve, performance of the model, and scalability of the model.

Название: Anatomy of Deep Learning Principles: Writing a Deep Learning Library from Scratch
Автор: Hongwei Dong
Издательство: Independently published
Год: 2023
Страниц: 664
Язык: английский
Формат: epub
Размер: 22.1 MB

This book introduces the basic principles and implementation process of Deep Learning in a simple way, and uses Python's Numpy library to build its own Deep Learning library from scratch instead of using existing Deep Learning libraries. On the basis of introducing basic knowledge of Python programming, calculus, and probability statistics, the core basic knowledge of Deep Learning such as regression model, neural network, convolutional neural network, recurrent neural network, and generative network is introduced in sequence according to the development of Deep Learning. While analyzing the principle in a simple way, it provides a detailed code implementation process. It is like not teaching you how to use weapons and mobile phones, but teaching you how to make weapons and mobile phones by yourself. This book is not a tutorial on the use of existing Deep Learning libraries, but an analysis of how to develop Deep Learning libraries from 0. This method of combining the principle from 0 with code implementation can enable readers to better understand the basic principles of Deep Learning and the design ideas of popular Deep Learning libraries.

Название: Тайная жизнь программ. Как создать код, который понравится вашему компьютеру
Автор: Джoнaтaн Cтeйнxapт
Издательство: Питер
Год: 2023
Страниц: 528
Язык: русский
Формат: pdf
Размер: 13.1 MB

Знакомы ли вы с технологиями, лежащими в основе вашей собственной программы? Почему «правильный» код не хочет работать? Истина проста и банальна — нужно сразу создавать код, который будет работать хорошо и не будет прятать в себе трудноуловимые ошибки. Для этого Джонатан Стейнхарт исследует фундаментальные концепции, лежащие в основе работы компьютеров. Он рассматривает аппаратное обеспечение, поведение программ на определенных устройствах, чтобы показать, как на самом деле должен работать ваш код. Узнайте, что на самом деле происходит, когда вы запускаете код на компьютере, — и вы научитесь программировать лучше и эффективнее.

Название: R for Data Analysis in easy steps, 2nd edition
Автор: Mike McGrath
Издательство: In Easy Steps Limited
Год: 2023
Страниц: 121
Язык: английский
Формат: epub
Размер: 18.97 MB

The R language is widely used by statisticians for data analysis, and the popularity of R programming has therefore increased substantially in recent years. The emerging Internet of Things (IoT) gathers increasing amounts of data that can be analyzed to gain useful insights into trends. R for Data Analysis in easy steps, 2nd edition has an easy-to-follow style that will appeal to anyone who wants to produce graphic visualizations to gain insights from gathered data. The book begins by explaining core programming principles of the R programming language, which stores data in “vectors” from which simple graphs can be plotted. Next, it describes how to create “matrices” to store and manipulate data from which graphs can be plotted to provide better insights. This book then demonstrates how to create “data frames” from imported data sets, and how to employ the “Grammar of Graphics” to produce advanced visualizations that can best illustrate useful insights from your data. R for Data Analysis in easy steps, 2nd edition contains separate chapters on the major features of the R programming language. There are complete example programs that demonstrate how to create Line graphs, Bar charts, Histograms, Scatter graphs, Box plots, and more. The code for each R script is listed, together with screenshots that illustrate the actual output when that script has been executed. The free, downloadable example R code is provided for clearer understanding.

Название: The Well-Grounded Python Developer: How the pros use Python and Flask (Final Release)
Автор: Doug Farrel
Издательство: Manning Publications
Год: 2023
Страниц: 298
Язык: английский
Формат: pdf (true)
Размер: 10.0 MB

If you’re new to Python, it can be tough to understand when, where, and how to use all its language features. This friendly guide shows you how the Python ecosystem fits together, and grounds you in the skills you need to continue your journey to being a software developer. The Well-Grounded Python Developer builds on Python skills you’ve learned in isolation and shows you how to unify them into a meaningful whole. It helps you understand the dizzying array of libraries and teaches important concepts, like modular construction, APIs, and the design of a basic web server. As you work through this practical guide, you’ll discover how all the bits of Python link up as you build and modify a typical web server application—the kind of web app that’s in high demand by modern businesses. As a new programmer, you’re happy just to see your code run. A professional developer, on the other hand, needs to create software that runs reliably. It must be fast, maintainable, scalable, secure, well designed and documented, easy for others to update, and quick to ship. This book teaches you the skills you need to go from Python programmer to Python developer. For experienced beginners who want to learn professional-level skills.

Название: Designing Deep Learning Systems: A software engineer's guide (Final Release)
Автор: Chi Wang, Donald Szeto
Издательство: Manning Publications
Год: 2023
Страниц: 362
Язык: английский
Формат: pdf (true)
Размер: 14.1 MB

A vital guide to building the platforms and systems that bring Deep Learning models to production. Deep Learning systems are the components and infrastructure essential to supporting a deep learning model in a production environment. Written especially for software engineers with minimal knowledge of deep learning’s design requirements, Designing Deep Learning Systems is full of hands-on examples that will help you transfer your software development skills to creating these deep learning platforms. You’ll learn how to build automated and scalable services for core tasks like dataset management, model training/serving, and hyperparameter tuning. This book is the perfect way to step into an exciting—and lucrative—career as a Deep Learning engineer. To be practically usable, a deep learning model must be built into a software platform. As a software engineer, you need a deep understanding of deep learning to create such a system. Th is book gives you that depth. For software developers and engineering-minded data scientists. Examples in Java and Python.