Litgu.ru - Литературный Гуру

Название: Deep Cognitive Networks: Enhance Deep Learning by Modeling Human Cognitive Mechanism
Автор: Yan Huang, Liang Wang
Издательство: Springer
Серия: SpringerBriefs in Computer Science
Год: 2023
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

Although Deep Learning models have achieved great progress in vision, speech, language, planning, control, and many other areas, there still exists a large performance gap between deep learning models and the human cognitive system. Many researchers argue that one of the major reasons accounting for the performance gap is that Deep Learning models and the human cognitive system process visual information in very different ways. To mimic the performance gap there has been a trend to model various cognitive mechanisms from cognitive neuroscience, e.g., attention, memory, reasoning, and decision, based on Deep Learning models. This book unifies these new kinds of Deep Learning models and calls them deep cognitive networks, which model various human cognitive mechanisms based on Deep Learning models. As a result, various cognitive functions are implemented, e.g., selective extraction, knowledge reuse, and problem solving, for more effective information processing.

Название: Artificial Intelligence for Students: A comprehensive overview of AI's foundation, applicability, and innovation
Автор: Vibha Pandey
Издательство: BPB Publications
Год: 2023
Страниц: 249
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

A multifaceted approach to develop an understanding of AI and its potential applications. Artificial Intelligence (AI) is a discipline in Computer Science that focuses on developing intelligent machines, machines that can learn and then teach themselves. If you are interested in AI, this book can definitely help you prepare for future careers in AI and related fields. The book is aligned with the CBSE course, which focuses on developing employability and vocational competencies of students in skill subjects. The book is an introduction to the basics of AI. It is divided into three parts – AI-informed, AI-inquired and AI-innovate. It will help you understand AI's implications on society and the world. You will also develop a deeper understanding of how it works and how it can be used to solve complex real-world problems. Additionally, the book will also focus on important skills such as problem scoping, goal setting, data analysis, and visualization, which are essential for success in AI projects. Lastly, you will learn how decision trees, neural networks, and other AI concepts are commonly used in real-world applications.

Название: The AI-Powered Productivity Handbook
Автор: Jamal Faisal Almutawa
Издательство: Independently published
Год: 2023
Страниц: 167
Язык: английский
Формат: epub (true)
Размер: 45.1 MB

Unleash the power of productivity and revolutionize your work process with this essential guide. With cutting-edge techniques and tools, you can transform your efficiency and shorten delivery time from days to minutes. Using popular Artificial Intelligence (AI) platforms, including ChatGPT, this book shows you how to achieve superhuman productivity by leveraging AI technology to automate the heavy lifting. From personal to professional success, this book is your key to unlocking your full potential. Don't wait, start your productivity journey today. This book focuses on utilizing AI, particularly ChatGPT, along with other platforms like DALL-E and Midjourney. The book extensively employs AI for various purposes such as providing prompt examples and generating results, suggesting new ideas, proofreading, rephrasing, and other functions. Writing this book with the assistance of AI was a delightful experience, and I hope you enjoy reading it as much as I enjoyed creating it.

Название: Graph Data Science For Dummies, 2nd Neo4j Special Edition
Автор: Dr. Alicia Frame, Zach Blumenfeld
Издательство: For Dummies
Год: 2022
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

We are passionate about the utility and importance of Graph Data Science and graph analytics, so we wrote this book to help organizations better leverage graphs so they can make new discoveries and develop intelligent solutions faster. In this book, we focus on the commercial applications of graph analysis and graph-enhanced Machine Mearning (ML), which takes the form of Graph Data Science. We also use Neo4j graph technology to illustrate a graph data science platform. You take a quick look at graph data science and its uses before covering the journey of graph data science adoption. You also review Neo4j technology as a graph data science platform and walk through a fraud detection example. Graph approaches to data are exploding in the commercial world to better reveal meaning in data as well as forecast behavior of complex systems. This burst is due to the increasing connectedness of data, breakthroughs in scaling graph technology to enterprise-sized problems, excellent results when integrated with Machine Learning (ML) and Artificial Intelligence (AI) solutions, and more accessible tools for general analytics and Data Science teams.

Название: ChatGPT Empowers Your Prompt Engineering with AI Tools: Unleashing Infinite Possibilities/ GPT-4 Update
Автор: Davis Coleman
Издательство: Independently published
Год: 2023
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.2 MB

Are you looking for innovative ways to transform your prompt engineering projects?! Look no further than ChatGPT - the powerful natural language processing tool that's taking the world by storm. In this must-read ebook, you'll discover how to harness the power of ChatGPT to streamline your engineering workflows, improve collaboration, and unlock new levels of innovation. Whether you're a seasoned engineering professional or just getting started with AI technology, "ChatGPT Empowers Your Prompt Engineering with AI Tools - Unleashing Infinite Possibilities" is a must-read resource to unlocking the full potential of chatgpt for your engineering projects. Get your copy today! and discover how ChatGPT can help take your business to the next level.

Название: Fun with Machine Learning: Simplify the Data Science process by automating repetitive and complex tasks using AutoML
Автор: Arockia Liborious, Dr. Rik Das
Издательство: BPB Publications
Год: 2023
Страниц: 271
Язык: английский
Формат: pdf, epub (true)
Размер: 10.8 MB

Learn how to use AutoML to leverage Machine Learning for solving business problems. “Fun with Machine Learning” is an essential guide for anyone looking to learn about machine learning and how it can be used to make informed business decisions. The book covers the basics of Machine Learning, providing an overview of key concepts and terminology. To fully understand Machine Learning, it is important to have a basic understanding of statistics and mathematics. The book provides a simple introduction to these topics, making it easy for you to understand the core concepts. One of the key features of the book is its focus on AutoML tools. It introduces you to different AutoML tools and explains how to use them to simplify the data science processes. The book also shows how Machine Learning can be used to solve real-world business problems, such as predicting customer churn, detecting fraud, and optimizing marketing campaigns.

Название: Introduction to Transfer Learning: Algorithms and Practice
Автор: Jindong Wang, Yiqiang Chen
Издательство: Springer
Серия: Machine Learning: Foundations, Methodologies, and Applications
Год: 2023
Страниц: 333
Язык: английский
Формат: pdf (true), epub
Размер: 50.4 MB

Transfer learning is one of the most important technologies in the era of Artificial Intelligence and Deep Learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice. Machine Learning is a kind of important learning methodology of Artificial Intelligence, which has gained great proliferation in the past decades. Machine Learning makes it possible to learn knowledge from the data. Transfer learning, as an important branch of Machine Learning, focuses on the process of leveraging the learned knowledge to facilitate the learning of new ability, which increases the effectiveness and efficiency.

Название: Объекты. Стильное ООП
Автор: Нобак Маттиас
Издательство: Питер
Год: 2023
Формат: pdf
Страниц: 304
Размер: 16,6 Мб
Язык: русский

Хороший объектно-ориентированный код удобно читать, изменять и исправлять. Универсальные практики проектирования объектов, собранные в этой книге, позволят улучшить ваш стиль кодирования. Эти правила подойдут к любому объектно-ориентированному языку, они делают код максимально понятным и надежным, а также повышают производительность как индивидуальных разработчиков, так и команд. Книга «Объекты. Стильное ООП» познакомит вас с профессиональными техниками написания ОО-кода. Маттиас Нобак раскрывает правила создания объектов, определения методов, изменения и извлечения состояний и многое другое. Все примеры написаны на простом псевдокоде, который легко перевести в любой язык программирования. Кейс за кейсом вы изучите ключевые сценарии и задачи проектирования объектов, а затем шаг за шагом создадите простое веб-приложение, которое покажет, как должны взаимодействовать объекты разных типов.

Название: Explainable AI for Practitioners: Designing and Implementing Explainable ML Solutions
Автор: Michael Munn, David Pitman
Издательство: O’Reilly Media, Inc.
Год: 2023
Страниц: 279
Язык: английский
Формат: True PDF, True EPUB/Retail Copy
Размер: 39.0 MB

Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced Machine Learning engineers and data scientists will learn hands-on how these techniques work so that you'll be able to apply these tools more easily in your daily workflow. When developing Machine Learning (ML) models, I am sure all of you have asked the questions: Oh, how did it get that right? or That’s weird, why would it predict that? As software engineers, our first instinct is to trace through the code to find the answers. Unfortunately, this does not get us very far with ML models because their “code” is automatically generated, not human-readable, and may span a vast number (sometimes billions!) of parameters. One needs a special set of tools to understand ML models. Explainable AI (XAI) is a field of Machine Learning focused on developing and analyzing such tools.

Название: Advanced Data Structures and Algorithms: Learn how to enhance data processing with more complex and advanced data structures
Автор: Abirami A., Priya R.L.
Издательство: BPB Publications
Год: 2023
Страниц: 214
Язык: английский
Формат: pdf, epub (true)
Размер: 10.2 MB

Solve complex problems by performing analysis of algorithms or selecting suitable techniques for optimal performance. “Advanced Data Structures and Algorithms” is an important subject area in Computer Science that covers more complex and advanced topics related to data structures and algorithms. This book will teach you how to analyze algorithms to handle the difficulties of sophisticated programming. It will then help you understand how advanced data structures are used to store and manage data efficiently. Moving on, it will help you explore and work with Divide and Conquer techniques, Dynamic programming, and Greedy algorithms. Lastly, the book will focus on various String Matching Algorithms such as naïve string matching algorithms, Knuth–Morris–Pratt (KMP) Algorithm, and Rabin-Karp Algorithm. This book covers a collection of complex algorithms and helps to face the challenges in algorithmic analysis. Analysis of algorithms and handling sophisticated data structures focus on the fundamentals of the computer programming field.