Название: Deep Learning: From Big Data to Artificial Intelligence with R
Автор: Dr. Stéphane Tufféry
Издательство: Wiley
Год: 2023
Страниц: 542
Язык: английский
Формат: pdf (true)
Размер: 10.9 MB

A concise and practical exploration of key topics and applications in Data Science. In Deep Learning: From Big Data to Artificial Intelligence with R , expert researcher Dr. Stéphane Tufféry delivers an insightful discussion of the applications of deep learning and big data that focuses on practical instructions on various software tools and deep learning methods relying on three major libraries: MXNet, PyTorch, and Keras-TensorFlow. In the book, numerous, up-to-date examples are combined with key topics relevant to modern data scientists, including processing optimization, neural network applications, natural language processing, and image recognition. Classroom-tested and intuitively organized, Deep Learning: From Big Data to Artificial Intelligence with R offers complimentary access to a companion website that provides R and Python source code for the examples offered in the book.

Название: Machine Learning on Commodity Tiny Devices: Theory and Practice
Автор: Song Guo, Qihua Zhou
Издательство: CRC Press
Год: 2023
Страниц: 268
Язык: английский
Формат: pdf (true)
Размер: 30.3 MB

This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. It presents on-device learning techniques covering model-level neural network design, algorithm-level training optimization, and hardware-level instruction acceleration. Analyzing the limitations of conventional in-cloud computing would reveal that on-device learning is a promising research direction to meet the requirements of edge intelligence applications. As to the cutting-edge research of TinyML, implementing a high-efficiency learning framework and enabling system-level acceleration is one of the most fundamental issues. This book presents a comprehensive discussion of the latest research progress and provides system-level insights on designing TinyML frameworks, including neural network design, training algorithm optimization and domain-specific hardware acceleration. It identifies the main challenges when deploying TinyML tasks in the real world and guides the researchers to deploy a reliable learning system.

Название: Building Feature Extraction with Machine Learning: Geospatial Applications
Автор: Bharath H. Aithal, Prakash P.S.
Издательство: CRC Press
Год: 2023
Страниц: 145
Язык: английский
Формат: pdf (true)
Размер: 13.2 MB

Big geospatial datasets created by large infrastructure projects require massive computing resources to process. Feature extraction is a process used to reduce the initial set of raw data for manageable image processing, and Machine Learning (ML) is the science that supports it. This book focuses on feature extraction methods for optical geospatial data using ML. It is a practical guide for professionals and graduate students who are starting a career in information extraction. It explains spatial feature extraction in an easy-to-understand way and includes real case studies on how to collect height values for spatial features, how to develop 3D models in a map context, and others. Explains the methods for estimating object height from optical satellite remote sensing images using Python.

Название: Normalization Techniques in Deep Learning
Автор: Lei Huang
Издательство: Springer
Год: 2022
Страниц: 117
Язык: английский
Формат: pdf (true), epub
Размер: 13.5 MB

This book presents and surveys normalization techniques with a deep analysis in training deep neural networks. In addition, the author provides technical details in designing new normalization methods and network architectures tailored to specific tasks. Normalization methods can improve the training stability, optimization efficiency, and generalization ability of deep neural networks (DNNs) and have become basic components in most state-of-the-art DNN architectures. The author provides guidelines for elaborating, understanding, and applying normalization methods. This book is ideal for readers working on the development of novel deep learning algorithms and/or their applications to solve practical problems in computer vision and machine learning tasks. The book also serves as a resource researchers, engineers, and students who are new to the field and need to understand and train DNNs.

Название: Пять строк кода. Роберт Мартин рекомендует
Автор: Кристиан Клаусен
Издательство: Питер
Год: 2023
Страниц: 359
Язык: русский
Формат: pdf
Размер: 10.9 MB

В каждой кодовой базе есть ошибки и слабые места, которые нужно найти и исправить. Правильный рефакторинг сделает ваш код элегантным, удобным для чтения и простым в обслуживании. Познакомьтесь с уникальным подходом, позволяющим реализовать любой метод в пяти строках кода. И не забывайте про тайну, хорошо известную большинству senior-разработчиков: иногда проще ухудшить код и вернуться к его исправлению позже. «Пять строк кода» — это свежий взгляд на рефакторинг для разработчиков любого уровня. Вы узнаете, когда проводить рефакторинг, как использовать паттерны, а также научитесь определять признаки, которые говорят о том, что код необходимо удалить. Для разработчиков всех уровней. В примерах используется доступный и понятный синтаксис TypeScript, который позволяет перейти к любому языку высокого уровня.

Название: Natural Language Processing in Action, 2nd Edition (MEAP v.6)
Автор: Hobson Lane
Издательство: Manning Publications
Год: 2022
Страниц: 359
Язык: английский
Формат: pdf (true)
Размер: 27.4 MB

Develop your NLP skills from scratch! This revised bestseller now includes coverage of the latest Python packages, Transformers, the HuggingFace packages, and chatbot frameworks. Natural Language Processing in Action has helped thousands of data scientists build machines that understand human language. In this new and revised edition, you’ll discover state-of-the art NLP models like BERT and HuggingFace transformers, popular open-source frameworks for chatbots, and more. As you go, you’ll create projects that can detect fake news, filter spam, and even answer your questions, all built with Python and its ecosystem of data tools.

Название: D3.js in Action, Third Edition (MEAP v.6)
Автор: Elijah Meeks, Anne-Marie Dufour
Издательство: Manning Publications
Год: 2022
Страниц: 275
Язык: английский
Формат: pdf (true)
Размер: 14.0 MB

Create stunning web-based data visualizations with D3.js. This totally-revised new edition of D3.js in Action guides you from simple charts to powerful interactive graphics. Learning D3 requires at least a minimal amount of literacy in front-end development. To get the most out of this book, you'll want to have previously learned the basics of front-end development. Being familiar with HTML elements, CSS selectors, and the main CSS properties will support your journey. You'll also need at least a beginner level of comprehension with jаvascript and its ES6 syntax. Knowing how to declare and manipulate strings, numbers, arrays, and objects will save you from many headaches, as well as understanding how to call and pass arguments to jаvascript functions.

Название: Evolutionary Intelligence for Healthcare Applications
Автор: T. Ananth Kumar, R. Rajmohan, M. Pavithra
Издательство: CRC Press
Год: 2023
Страниц: 136
Язык: английский
Формат: pdf (true)
Размер: 10.3 MB

This book highlights various evolutionary algorithm techniques for various medical conditions and introduces medical applications of evolutionary computation for real-time diagnosis.

Evolutionary Intelligence for Healthcare Applications presents how evolutionary intelligence can be used in smart healthcare systems involving big data analytics, mobile health, personalized medicine, and clinical trial data management. It focuses on emerging concepts and approaches and highlights various evolutionary algorithm techniques used for early disease diagnosis, prediction, and prognosis for medical conditions. The book also presents ethical issues and challenges that can occur within the healthcare system. In the recent two decades, the acceptance of metaheuristics, particularly swarm intelligence and evolutionary algorithms (EAs), has exploded. Researchers offer a plethora of algorithms and approaches every year, and they discover a growing number of innovative applications. When we consider our daily lives, it becomes apparent that intelligent systems play a greater part in our work or practical actions, and numerous changes have been noted over the past several years in terms of intelligent approaches, methods, and techniques. Currently, the discipline of metaheuristics is having considerable influence on the spectrum of healthcare, particularly in illness diagnosis and medicine discovery. Genetic intelligence has evolved as a new-generation technique belonging to the evolutionary computing category.

Название: NumPy : From Basic to Advance : for Machine Learning
Автор: Karan Singh Bisht
Издательство: Independently published
Год: 2022
Страниц: 200
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.3 MB

NumPy, which stands for Numerical Python, is a library consisting of multidimensional array objects and a collection of routines for processing those arrays. Using NumPy, mathematical and logical operations on arrays can be performed. NumPy is a Python package. It stands for ‘Numerical Python’. It is a library consisting of multidimensional array objects and a collection of routines for processing of array. It also has functions for working in domain of linear algebra, fourier transform, and matrices. NumPy is often used along with packages like SciPy (Scientific Python) and Matplotlib (plotting library). This combination is widely used as a replacement for MatLab, a popular platform for technical computing. However, Python alternative to MatLab is now seen as a more modern and complete programming language. It is open-source, which is an added advantage of NumPy.

Название: Introduction to Financial Derivatives with Python
Автор: Elisa Alos, Raul Merino
Издательство: CRC Press
Год: 2023
Страниц: 253
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Introduction to Financial Derivatives with Python is an ideal textbook for an undergraduate course on derivatives, whether on a finance, economics, or financial mathematics programme. As well as covering all of the essential topics one would expect to be covered, the book also includes the basis of the numerical techniques most used in the financial industry, and their implementation in Python. At every stage and chapter, the reader will find engaging numerical demonstrations and exercises that further clarify the theory behind derivatives pricing. Furthermore, the numerical examples are coded in Python, which is now one of the most widely used programming languages at banks and asset managers. After reading the next two-hundred or so pages, the student will have gained the necessary theoretical background as well as hands-on programming experience, which is an indispensable skill in quantitative finance.