Название: Programming Language Design and Implementation
Автор: Torben Ægidius Mogensen
Издательство: Springer
Год: 2022
Страниц: 333
Язык: английский
Формат: pdf (true), epub
Размер: 13.5 MB

This textbook is intended as a guide for programming-language designers and users to better help them understand consequences of design decisions. The text aims to provide readers with an overview of the design space for programming languages and how design choices affect implementation. It is not a classical compilers book, as it assumes the reader is familiar with basic compiler implementation techniques; nor is it a traditional comparative programming languages book, because it does not go into depth about any particular language, instead taking examples from a wide variety of programming languages to illustrate design concepts. Exceptionally comprehensive in approach, this book explores the major issues in both design and implementation of modern programming languages and provides a basic introduction to the underlying theoretical models on which these languages are based. The emphasis throughout is on fundamental concepts—readers learn important ideas, not minor language differences--but several languages are highlighted in sufficient detail to enable readers to write programs that demonstrate the relationship between a source program and its execution behavior--e.g., C, C++, JAVA, ML, LISP, Prolog, Smalltalk, Postscript, HTML, PERL, FORTRAN, Ada, COBOL, BASIC SNOBOL4, PL/I, Pascal.

Название: Artificial Neural Networks and Structural Equation Modeling: Marketing and Consumer Research Applications
Автор: Alhamzah Alnoor, Khaw Khai Wah, Azizul Hassan
Издательство: Springer
Год: 2022
Страниц: 336
Язык: английский
Формат: pdf (true), epub
Размер: 10.4 MB

This book goes into a detailed investigation of adapting artificial neural network (ANN) and structural equation modeling (SEM) techniques in marketing and consumer research. The aim of using a dual-stage SEM and ANN approach is to obtain linear and non-compensated relationships because the ANN method captures non-compensated relationships based on the black box technology of artificial intelligence. Hence, the ANN approach validates the results of the SEM method. In addition, such the novel emerging approach increases the validity of the prediction by determining the importance of the variables. Consequently, the number of studies using SEM-ANN has increased, but the different types of study cases that show customization of different processes in ANNs method combination with SEM are still unknown, and this aspect will be affecting to the generation results. Thus, there is a need for further investigation in marketing and consumer research. This book bridges the significant gap in this research area.

Название: Statistical Foundations of Actuarial Learning and its Applications
Автор: Mario V. Wuthrich, Michael Merz
Издательство: Springer
Год: 2023
Страниц: 611
Язык: английский
Формат: pdf (true)
Размер: 24.0 MB

Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern Machine Learning tools such as neural networks and text recognition to improve predictive modeling with complex features. In the sequel, we introduce Deep Learning models. In this chapter these Deep Learning models will be based on fully-connected feed-forward neural networks. We present these networks as an extension of Generalized Linear Models (GLMs). These networks perform feature engineering themselves. We discuss how networks achieve this, and we explain how networks are used for predictive modeling. There is a vastly growing literature on Deep Learning with networks, the classical reference is the book of Goodfellow et al., but also the numerous tutorials around the open-source Deep Learning libraries TensorFlow, Keras or PyTorch give an excellent overview of the state-of-the-art in this field.

Название: Machine Learning for Cyber Security
Автор: Preeti Malik, Lata Nautiyal, Mangey Ram
Издательство: De Gruyter
Год: 2023
Страниц: 160
Язык: английский
Формат: pdf (true), epub
Размер: 22.8 MB

Cyber threats today are one of the expensive losses that an organization can face. Today, it is impossible to deploy effective cybersecurity technology without relying heavily on advanced techniques like Machine Learning and Deep Learning. Cybersecurity is a growing challenge in the era of Internet. This book addresses questions of how Machine Learning methods can be used to advance cybersecurity objectives, including detection, modeling, monitoring, and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between Machine Learning and cybersecurity communities, it discusses topics covering a wide range of modern and practical Machine Learning techniques, frameworks, and development tools to enable readers to engage with the cutting-edge research across various aspects of cybersecurity. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points. This cybersecurity book presents and demonstrates popular and successful Artificial Intelligence (AI) approaches and models that you can adapt to detect potential attacks and protect your corporate systems.

Название: Machine Learning Algorithms for Signal and Image Processing
Автор: Deepika Ghai, Suman Lata Tripathi, Sobhit Saxena
Издательство: Wiley-IEEE Press
Год: 2023
Страниц: 487
Язык: английский
Формат: pdf (true)
Размер: 18.7 MB

Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing. Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve Machine Learning tasks.

Название: Building Browser Extensions: Create Modern Extensions for Chrome, Safari, Firefox, and Edge
Автор: Matt Frisbie
Издательство: Apress
Год: 2023
Страниц: 561
Язык: английский
Формат: pdf, epub
Размер: 21.5 MB

Almost all web developers today have plenty of experience with building regular web page apps, but a lot of that knowledge doesn't transfer over when it comes to creating browser extensions. This book provides a complete reference for how to build modern browser extensions. Creating and deploying a browser extension is more like building a mobile app than a website. When you start building an extension you'll often find there are a large number of new concepts and idiosyncrasies to wrangle with. This book reveals how to successfully navigate around these obstacles and how to take advantage of the limited resources available. You'll see how a browser extensions work, their component pieces, and how to build and deploy them. Additionally, you'll review all the tricky bits of extension development that most developers have to learn through trial and error. Build a browser extension using modern jаvascript frameworks.

Название: Beginning Salesforce DX: Versatile and Resilient Salesforce Application Development
Автор: Ivan Harris
Издательство: Apress
Год: 2022
Страниц: 558
Язык: английский
Формат: pdf, epub
Размер: 21.8 MB

Refer to the practical guidance provided in this book to develop Salesforce custom applications in a more agile, collaborative, and resilient way using Salesforce Developer Experience (DX). You will learn how to use the Salesforce Command Line Interface (CLI) to simplify working with projects, metadata, data and orgs. The CLI integrates with your development tools of choice such as Visual Studio Code, and CI/CD tools to implement DevOps pipelines. Readers will also gain an understanding of the package development model, which improves application quality and maintainability by grouping metadata into highly cohesive, loosely coupled containers.

Название: Graph-Powered Analytics and Machine Learning with TigerGraph: Driving Business Outcomes with Connected Data (Eighth Release)
Автор: Victor Lee, Phuc Kien Nguyen, Xinyu Chang
Издательство: O’Reilly Media, Inc.
Год: 2022-11-22
Страниц: 149
Язык: английский
Формат: epub
Размер: 14.96 MB

With the rapid rise of graph databases, organizations are now implementing advanced analytics and Machine Learning solutions to help drive business outcomes. This practical guide shows data scientists, data engineers, architects, and business analysts how to get started with a graph database using TigerGraph, one of the leading graph database models available. You'll explore a three-stage approach to deriving value from connected dаta: connect, analyze, and learn. Victor Lee, Xinyu Chan, and Gaurav Deshpande from TigerGraph present real use cases covering several contemporary business needs. By diving into hands-on exercises using TigerGraph Cloud, you'll quickly become proficient at designing and managing advanced analytics and Machine Learning solutions for your organization.

Название: Intelligent Systems and Machine Learning for Industry: Advancements, Challenges, and Practices
Автор: P.R Anisha, C. Kishor Kumar Reddy, Nhu Gia Nguyen
Издательство: CRC Press
Год: 2023
Страниц: 362
Язык: английский
Формат: pdf (true)
Размер: 26.5 MB

The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics.

Название: Applied Recommender Systems with Python: Build Recommender Systems with Deep Learning, NLP and Graph-Based Techniques
Автор: Akshay Kulkarni, Adarsha Shivananda, Anoosh Kulkarni
Издательство: Apress
Год: 2023
Страниц: 257
Язык: английский
Формат: pdf (true), epub
Размер: 43.9 MB

This book will teach you how to build recommender systems with Machine Learning algorithms using Python. Recommender systems have become an essential part of every internet-based business today. You'll start by learning basic concepts of recommender systems, with an overview of different types of recommender engines and how they function. Next, you will see how to build recommender systems with traditional algorithms such as market basket analysis and content- and knowledge-based recommender systems with NLP. The authors then demonstrate techniques such as collaborative filtering using matrix factorization and hybrid recommender systems that incorporate both content-based and collaborative filtering techniques. This is followed by a tutorial on building machine learning-based recommender systems using clustering and classification algorithms like K-means and random forest. The last chapters cover NLP, deep learning, and graph-based techniques to build a recommender engine. Each chapter includes data preparation, multiple ways to evaluate and optimize the recommender systems, supporting examples, and illustrations.