Название: Kubernetes for Developers (MEAP v14)
Автор: William Denniss
Издательство: Manning Publications
Год: 2023
Страниц: 279
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Kubernetes for Developers is a hands-on guide to taking your first steps into Kubernetes using the powerful Google Kubernetes Engine service. Kubernetes for Developers is a clear and practical beginner’s guide that shows you just how easy, flexible, and cost-effective it can be to make the switch to Kubernetes deployment even for small to medium-sized applications.

Название: A Pythonic Adventure: From Python basics to a working web app (MEAP v7)
Автор: Pavel Anni
Издательство: Manning Publications
Год: 2023
Страниц: 241
Язык: английский
Формат: pdf (true)
Размер: 13.0 MB

Learn Python the fun and easy way with your new friends Erik and Simon! This colorful book uses engaging questions and lively conversations to introduce computer programming to young readers one step at a time. A Pythonic Adventure listens in on the conversations between two aspiring Python programmers. The book’s dialogue helps young programmers understand complex concepts much more easily. Characters ask questions, make mistakes, and offer different solutions—just like in real life. Readers will develop fun and engaging Python applications, including a coffee shop app for taking orders and a LEGO minifigure exchange program. Best of all, A Pythonic Adventure dives deeper than other beginner books. Inside are important skills for any new software developer, such as how to plan an application, what to expect from users, and how to test code and check for errors. By the time they’re done reading, young learners will not only know how to write code, they’ll know how to think about problems like professional developers!

Название: Cloud Observability in Action (MEAP v10)
Автор: Michael Hausenblas
Издательство: Manning Publications
Год: 2023
Страниц: 234
Язык: английский
Формат: pdf (true)
Размер: 22.9 MB

Generate actionable insights about your cloud native systems. This book teaches you how to set up an observability system that learns from a cloud application’s signals, logging, and monitoring using free and open source tools. Cloud native, serverless, and containerized applications are made up of hundreds of moving parts. When something goes wrong, it’s not enough to just know there is a problem—you need to know where it is, what it is, and even how to fix it. Cloud Observability in Action shows you how to go beyond the traditional monitoring and build observability systems that turn application telemetry into actionable insight. A well-designed observability system provides insight into bugs and performance issues in cloud native applications. Often, observability is the difference between an error message and an explanation! You know exactly which service is affected, who’s responsible for its repair, and even how it can be optimized in the future.

Название: Regularization in Deep Learning (MEAP v6)
Автор: Peng Liu
Издательство: Manning Publications
Год: 2023
Страниц: 288
Язык: английский
Формат: pdf (true)
Размер: 18.1 MB

Make your Deep Learning models more generalized and adaptable! These practical regularization techniques improve training efficiency and help avoid overfitting errors. Regularization in Deep Learning teaches you how to improve your model performance with a toolbox of regularization techniques. It covers both well-established regularization methods and groundbreaking modern approaches. Each technique is introduced using graphics, illustrations, and step-by-step coding walkthroughs that make complex math easy to follow. One of the most important goals in building Machine Learning and especially Deep Learning models is to achieve good generalization performance in the test dataset. The training task is considered to be completed when we have obtained a generalizable model, often with the help of proper regularization in the training process. While the theory of generalization still remains a mystery, it is an active research area with new insights being proposed.

Название: Deep Learning with JAX (MEAP v6)
Автор: Grigory Sapunov
Издательство: Manning Publications
Год: 2023
Страниц: 211
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Accelerate deep learning and other number-intensive tasks with JAX, Google’s awesome high-performance numerical computing library. JAX is a Python mathematics library with a NumPy interface developed by Google. It is heavily used for machine learning research, and it seems that JAX has already become the #3 Deep Learning framework (after TensorFlow and PyTorch). It also became the main Deep Learning framework in companies such as DeepMind, and more and more of Google’s own research use JAX. JAX promotes a functional programming paradigm in Deep Learning. It has powerful function transformations such as taking gradients of a function, JIT-compilation with XLA, auto-vectorization, and parallelization. JAX supports GPU and TPU and provides great performance. Deep Learning with JAX is a hands-on guide to using JAX for Deep Learning and other mathematically-intensive applications. Google Developer Expert Grigory Sapunov steadily builds your understanding of JAX’s concepts. The engaging examples introduce the fundamental concepts on which JAX relies and then show you how to apply them to real-world tasks.

Название: Компьютерная энциклопедия для школьников и их родителей
Автор: Борман Дж.
Издательство: Питер
ISBN: 5-88782-115-9
Год издания: 1996
Страниц: 208
Язык: Русский
Формат: pdf
Размер: 29 Мб

Пожалуй настало время нашим мальчишкам и девчонкам блеснуть своей эрудицией на уроке информатики, а папам и мамам — найти общий "компьютерный" язык со своими детьми.
Перевод замечательной книги Дж. Борман, выполненный по лицензии издательства Barron"s, поможет вам в этом.

Название: Artificial Intelligence in Models, Methods and Applications
Автор: Olga Dolinina, Igor Bessmertny, Alexander Brovko, Vladik Kreinovich
Издательство: Springer
Год: 2023
Страниц: 694
Язык: английский
Формат: pdf (true)
Размер: 21.3 MB

This book presents new perspective research results: models, methods, algorithms and applications in the field of Artificial Intelligence (AI). Particular emphasis is given to the medical applications - medical images recognition, development of the expert systems which could be interesting for the AI researchers as well for the physicians looking for the new ideas in medicine. The central audience of the book are researchers, industrial practitioners, students specialized in the Artificial Intelligence. The Chapter "Development of a Program Code Review System Using Machine Learning Methods" presents a description of the developed approach and service for analyzing source code in Python. The service reduces the time for code review due to partial automation. The FastText algorithm is used to obtain vector representations of source code texts. A pre-trained neural network language model based on the transformer architecture was used to derive a possible natural language function assignment.

Название: Building Knowledge Graphs: A Practitioner’s Guide (6th Early Release)
Автор: Jesus Barrasa, Maya Natarajan, Jim Webber
Издательство: O’Reilly Media, Inc.
Год: 2023-04-24
Страниц: 335
Язык: английский
Формат: epub
Размер: 24.0 MB

Incredibly useful, knowledge graphs help organizations keep track of medical research, cybersecurity threat intelligence, GDPR compliance, web user engagement, and much more. They do so by saving interlinked descriptions of entities (objects, events, situations, or abstract concepts) while encoding the semantics underlying the terminology. How do you create a knowledge graph? And how do you move it from theory into practice? Graph data has become ubiquitous in the last decade. Graphs underpin everything from consumer-facing systems like navigation and social networks to critical infrastructure like supply chains and policing. A consistent theme has emerged: applying knowledge in context is the single most powerful tool that most businesses have. Through research and experience, a set of patterns and practices called knowledge graphs has been developed to support extracting knowledge from data of all types and in all sources, from systems of record to frozen data lakes to application logs. This book is for information technology professionals who are interested in building and operating knowledge graphs within their businesses.

Название: Introducing Spring Framework 6: Learning and Building Java-based Applications With Spring, Second Edition
Автор: Felipe Gutierrez, Joseph B. Ottinger
Издательство: Apress
Год: 2022
Страниц: 219
Язык: английский
Формат: pdf (true), epub (true)
Размер: 10.2 MB

Spring Framework 6 remains - by far - the leading de-facto "out of the box" practical Java meta application development framework for building complex enterprise, cloud-native applications as well as web applications and microservices. Introducing Spring Framework 6 is your hands-on tutorial guide for learning the Spring Framework 6 from top to bottom, and allows you to build an example application along the way from the ground-up. As you learn the Spring Framework over the course of this book, you’ll incrementally build your first Spring application piece-by-piece as you learn each module, project or component of the Spring Framework and its extensions and ecosystem. As you learn the various fundamentals, you'll then apply them immediately to your Spring application. This Spring application, My Documents, enables you to learn by doing.

Название: Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techniques, 2nd Edition
Автор: Sayan Mukhopadhyay, Pratip Samanta
Издательство: Apress
Год: 2023
Страниц: 259
Язык: английский
Формат: pdf (true), epub (true)
Размер: 13.5 MB

Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing (NLP), and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build Machine Learning and Deep Learning models using transfer learning.