Название: Graph Neural Networks in Action (MEAP v8)
Автор: Keita Broadwater
Издательство: Manning Publications
Год: 2023
Страниц: 404
Язык: английский
Формат: epub
Размер: 32.6 MB

A hands-on guide to powerful graph-based Deep Learning models! Learn how to build cutting-edge graph neural networks for recommendation engines, molecular modeling, and more. Graph Neural Networks in Action teaches you to create powerful Deep Learning models for working with graph data. You’ll learn how to both design and train your models, and how to develop them into practical applications you can deploy to production. Go hands-on and explore relevant real-world projects as you dive into graph neural networks perfect for node prediction, link prediction, and graph classification. Inside this practical guide, you’ll explore common graph neural network architectures and cutting-edge libraries, all clearly illustrated with well-annotated Python code. Graph neural networks expand the capabilities of Deep Learning beyond traditional tabular data, text, and images. This exciting new approach brings the amazing capabilities of deep learning to graph data structures, opening up new possibilities for everything from recommendation engines to pharmaceutical research. For Python programmers familiar with Machine Learning and the basics of Deep Learning.

Название: Fundamentals of Supervised Machine Learning: With Applications in Python, R, and Stata
Автор: Giovanni Cerulli
Издательство: Springer
Год: 2023
Страниц: 416
Язык: английский
Формат: pdf (true), epub
Размер: 63.8 MB

This book presents the fundamental theoretical notions of supervised Machine Learning along with a wide range of applications using Python, R, and Stata. It provides a balance between theory and applications and fosters an understanding and awareness of the availability of Machine Learning methods over different software platforms. After introducing the Machine Learning basics, the focus turns to a broad spectrum of topics: model selection and regularization, discriminant analysis, nearest neighbors, support vector machines, tree modeling, artificial neural networks, Deep Learning, and sentiment analysis. Each chapter is self-contained and comprises an initial theoretical part, where the basics of the methodologies are explained, followed by an applicative part, where the methods are applied to real-world datasets. Numerous examples are included and, for ease of reproducibility, the Python, R, and Stata codes used in the text, along with the related datasets, are available online.

Название: Become A Ninja With Angular (v17.0.0)
Автор: Ninja Squad
Издательство: Ninja Squad
Год: 2023-11-08
Страниц: 346
Язык: английский
Формат: pdf (true), epub, mobi
Размер: 10.1 MB

Книга "Стань ниндзя с Angular" поможет программистам понять философию Angular на практике (в настоящее время 17.0.2), новые инструменты (такие как ES2015, TypeScript, SystemJS, Webpack, Angular CLI ...) и каждую часть инфраструктуры. К концу чтения данного руководства вы сможете начать свой проект и создавать свои удивительные приложения!

Название: Telegram Bot. Руководство по созданию бота в мессенджере Телеграм
Автор: Артем Демиденко
Издательство: Литрес
Год: 2023
Формат: pdf, rtf
Размер: 10 Мб
Страниц: 30
Язык: Русский

Эта книга является практическим руководством по созданию бота для Telegram с использованием языка программирования Python. В ней описываются основные шаги для создания бота, такие как регистрация и получение токена, установка и настройка необходимых библиотек, создание функций бота и его запуск. Также рассмотрены дополнительные функции, которые можно добавить в бота, такие как отправка фотографий и видео, использование клавиатуры для быстрого ответа на сообщения, интеграция с другими сервисами и машинное обучение для распознавания сообщений.

Название: Kubernetes Cookbook: Building Cloud Native Applications, 2nd Edition (Final)
Автор: Sameer Naik, Sébastien Goasguen, Jonathan Michaux
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 301
Язык: английский
Формат: pdf, epub (true)
Размер: 10.1 MB

Kubernetes is the de facto standard for container orchestration and distributed applications management across a microservices framework. With this practical cookbook, you'll learn hands-on Kubernetes recipes for automating the deployment, scaling, and operations of application containers across clusters of hosts. In this fully updated second edition, Sameer Naik, Sébastien Goasguen, and Jonathan Michaux from TriggerMesh provide a problem-solution-discussion format with easy lookups to help you find the detailed answers you need—fast. Kubernetes lets you deploy your applications quickly and predictably, so you can efficiently respond to customer demand. This cookbook delivers the essential knowledge that developers and system administrators need to get there. With this book, we want to help you solve concrete problems around Kubernetes. We’ve compiled more than 100 recipes covering topics such as setting up a cluster, managing containerized workloads using Kubernetes API objects, using storage primitives, configuring security, and plenty more. This book was written for anyone who belongs somewhere in the DevOps spectrum. You might be an application developer who is required to occasionally interact with Kubernetes, or a platform engineer creating reusable solutions for other engineers in your organization, or anywhere in between. This book will help you navigate your way successfully through the Kubernetes jungle, from development to production.

Название: Generative AI on AWS: Building Context-Aware Multimodal Reasoning Applications
Автор: Chris Fregly, Antje Barth, Shelbee Eigenbrode
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 309
Язык: английский
Формат: epub (true)
Размер: 42.1 MB

Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. A basic understanding of Python and deep learning frameworks such as TensorFlow or PyTorch should be sufficient to understand the code samples used throughout the book. Familiarity with AWS is not required to learn the concepts, but it is useful for some of the AWS-specific samples.

Название: Natural Language Processing: A Textbook With Python Implementation
Автор: Raymond S. T. Lee
Издательство: Springer
Год: 2024
Страниц: 454
Язык: английский
Формат: pdf (true)
Размер: 23,9 MB

This textbook presents an up-to-date and comprehensive overview of Natural Language Processing (NLP), from basic concepts to core algorithms and key applications. Further, it contains seven step-by-step NLP workshops (total length: 14 hours) offering hands-on practice with essential Python tools like NLTK, spaCy, TensorFlow Kera, Transformer and BERT. The objective of this book is to provide readers with a fundamental grasp of NLP and its core technologies, and to enable them to build their own NLP applications (e.g. Chatbot systems) using Python-based NLP tools. It is both a textbook and NLP tool-book intended for the following readers: undergraduate students from various disciplines who want to learn NLP; lecturers and tutors who want to teach courses or tutorials for undergraduate/graduate students on NLP and related AI topics; and readers with various backgrounds who want to learn NLP, and more importantly, to build workable NLP applications after completing its 14 hours of Python-based workshops. This book can be served as a textbook for undergraduates and postgraduate courses on Natural Language Processing, and a reference book for general readers who would like to learn key technologies and implement NLP applications with contemporary implementation tools such as NLTK, spaCy, TensorFlow, BERT, and Transformer technology.

Название: What Are AI Agents? When and How to Use LLM Agents
Автор: Benjamin Labaschin
Издательство: O’Reilly Media, Inc.
Год: 2024
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

AI agents represent the latest milestone in humanity's computational toolbox. Powered by large language models (LLMs) and the data they were trained on, AI agents are tools that let you interact with specialized LLMs to achieve more productive or creative workflows with less technical hassle. The last century in the history of computing has had many notable milestones: the invention of the computer; the development of the personal computer as we know it; the internet; the smart phone; machine learning; and cloud computing. Every few decades it seems societies are thrust forward, riding the wave of some new computational innovation. If you are reading this, then congratulations (or I’m sorry?), you are living during another one of these milestones in computational advancement. Code assistant agents are AI agents that are fueled by models specifically designed to help users like you write code more productively and efficiently. Popular code assistant agents include GitHub Copilot, Amazon CodeWhisperer, and Hugging Face’s StarCoder. Code assistant agents are tools designed to edit error-ridden code, autocomplete simple functions to common coding problems, or design templates for more difficult coding problems.

Название: Python GUI Development with PyQt: Mastering PyQt
Автор: Williams Asiedu
Издательство: Ouereila Publishing House
Год: 2023
Страниц: 183
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

"Python GUI Development with PyQt" is a comprehensive guide for software developers aiming to master graphical user interface creation using Python and PyQt. The book covers fundamental concepts such as widgets and layouts, progressing to advanced topics like custom widgets and multi-threading. Readers learn to design visually appealing interfaces using Qt Designer and implement functionality through Python code. Practical examples and projects reinforce learning, while best practices ensure the development of maintainable and efficient applications. The guide also addresses deployment strategies, helping developers package and distribute their PyQt applications across various operating systems. With an emphasis on real-world application, this book equips developers with the skills needed for effective GUI development in Python. Immersive in practicality, this book is laden with examples to ensure a profound grasp of every concept. It delves into the practical usage of PyQt libraries, spotlighting essential modules for constructing remarkable graphical user interfaces. With snippets of meticulously tested code, you’ll find ready-to-use segments that can be effortlessly copied and pasted into your integrated development environment (IDE). This book aspires to be your comprehensive guide in mastering the art of desktop application development with Python.

Название: Neural Networks with Python: Design CNNs, Transformers, GANs and capsule networks using Tensorflow and Keras
Автор: Mei Wong
Издательство: GitforGits
Год: November 2023
Страниц: 253
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

"Neural Networks with Python" serves as an introductory guide for those taking their first steps into neural network development with Python. It's tailored to assist beginners in understanding the foundational elements of neural networks and to provide them with the confidence to delve deeper into this intriguing area of Machine Learning. In this book, readers will embark on a learning journey, starting from the very basics of Python programming, progressing through essential concepts, and gradually building up to more complex neural network architectures. The book simplifies the learning process by using relatable examples and datasets, making the concepts accessible to everyone. You will be introduced to various neural network architectures such as Feedforward, Convolutional, and Recurrent Neural Networks, among others. Each type is explained in a clear and concise manner, with practical examples to illustrate their applications. The book emphasizes the real-world applications and practical aspects of neural network development, rather than just theoretical knowledge. By the end of your journey with this book, you will have a foundational understanding of neural networks within the Python ecosystem and be prepared to apply this knowledge to real-world scenarios.