Название: Designing Microservices (MEAP v5)
Автор: S. Ramesh
Издательство: Manning Publications
Год: 2023
Страниц: 251
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Start your microservices projects right! Choosing the best design patterns, tools, deployment strategies, and team structure will maximize innovation, agility, time to market, and reliability. Microservices designs allow individual components to be built and deployed as independent, single-purpose applications, each with its own data store. This approach can deliver business agility and software reliability, or it can easily flop without careful attention to APIs, communication, and cross-service concerns like transactions, state, and long-term maintenance. Designing Microservices teaches a reliable and repeatable design process to ensure you’re always getting the results you want from microservices. It introduces a lightweight DDD-inspired design tool that simplifies the modeling of your architecture that will be instantly familiar to anyone who’s worked with UML and responsibility mapping. You’ll learn to handle multi-faced commits across microservices, to refactor and deploy legacy apps without service downtime, and how to manage service patterns like consumer driven contracts. Easy-to-grok illustrations and explanations cut through the buzzwords and offer clear solutions for analytics, monitoring, testing, and more. For software architects, managers, analysts, and developers of all skill levels. No previous experience building microservices required.

Название: Unsupervised Learning with Generative AI (MEAP v7)
Автор: Vaibhav Verdhan
Издательство: Manning Publications
Год: 2023
Страниц: 374
Язык: английский
Формат: epub
Размер: 10.1 MB

Discover all-practical implementations of the key algorithms and models for handling unlabeled data. Full of case studies demonstrating how to apply each technique to real-world problems. Unsupervised Learning with Generative AI introduces mathematical techniques, key algorithms, and Python implementations that will help you build machine learning models for unannotated data. You’ll discover hands-off and unsupervised machine learning approaches that can still untangle raw, real-world datasets and support sound strategic decisions for your business. Don’t get bogged down in theory—the book bridges the gap between complex math and practical Python implementations, covering end-to-end model development all the way through to production deployment. You’ll discover the business use cases for machine learning and unsupervised learning, and access insightful research papers to complete your knowledge. Unsupervised Learning with Generative AI teaches you to apply a full spectrum of machine learning algorithms to raw data. You’ll master everything from kmeans and hierarchical clustering, to advanced neural networks like GANs and Restricted Boltzmann Machines. Each new algorithm is introduced with a case study for retail, aviation, banking, and more—and you’ll develop a Python solution to fix each of these real-world problems. At the end of each chapter, you’ll find quizzes, practice datasets, and links to research papers to help you lock in what you’ve learned and expand your knowledge. For developers and data scientists. Basic Python experience required.

Название: Чистый Python. Тонкости программирования для профи
Автор(ы): Дэн Бейдер
Издательство: Питер
Год: 2024
Страниц: 288
Формат: PDF
Размер: 14 Мб
Язык: русский

Изучение всех возможностей Python — сложная задача, а с этой книгой вы сможете сосредоточиться на практических навыках, которые действительно важны. Раскопайте «скрытое золото» в стандартной библиотеке Python и начните писать чистый код уже сегодня. Если у вас есть опыт работы со старыми версиями Python, вы сможете ускорить работу с современными шаблонами и функциями, представленными на Python 3.

Название: Distributed Machine Learning Patterns (Final Release)
Автор: Yuan Tang
Издательство: Manning Publications
Год: 2024
Страниц: 248
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Practical patterns for scaling Machine Learning from your laptop to a distributed cluster. Distributed Machine Learning Patterns teaches you how to scale Machine Learning models from your laptop to large distributed clusters. In it, you’ll learn how to apply established distributed systems patterns to Machine Learning projects, and explore new ML-specific patterns as well. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Real-world scenarios, hands-on projects, and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed Machine Learning pipelines. For data analysts, data scientists, and software engineers who know the basics of Machine Learning algorithms and running Machine Learning in production. Readers should be familiar with the basics of Bash, Python, and Docker.

Название: Специальные функции и определенные интегралы. Алгоритмы. Программы для микрокалькуляторов. Справочник
Автор: Цимринг Шулим Ефимович
Издательство: Радио и связь
Год: 1988
Формат: pdf, djvu
Страниц: 272
Размер: 12.2 Мб
Язык: русский

Содержит алгоритмы вычисления значений специальных функций вещественного и комплексного аргумента и соответствующие программы для микрокалькуляторов. Приведены алгоритмы и программы вычисления нулей специальных функций и нулей их производных, определенных интегралов, в том числе несобственных, и интегралов от функций комплексного переменного. В справочнике около 250 программ.

Название: Ruby on Rails Background Jobs with Sidekiq: Run Code Later without Complicating Your App
Автор: David Bryant Copeland
Издательство: The Pragmatic Programmers
Год: October 2023 (Version: P1.0)
Страниц: 106
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.2 MB

Sidekiq is a reliable, well-supported, high-performing way to run code in the background of any Rails app. This book will give you a solid, practical foundation for creating resilient, well-tested, self-healing code that uses background jobs. You'll be able to simulate real-world failure modes and learn how to write idempotent code that can be safely run with Sidekiq. Whether you need to offload slow code out of a controller action, or make a flaky API call more fault tolerant, Sidekiq is the way to do that. One of the best ways to improve your Rails app's performance is to use background jobs with Sidekiq. While Sidekiq is easy to get set up, you need to do more than just move code around to reap the benefits. In this book, you'll get solutions to what sort of code should go into a Sidekiq job and how to manage those jobs. Even though you just need a few lines of code to run a Sidekiq job, there is quite a bit of complexity hiding in the shadows. A Rails app with Sidekiq jobs is really a distributed system. It has all the same challenges as a massive microservices-based architecture.

Название: Hacks, Leaks, and Revelations: The Art of Analyzing Hacked and Leaked Data (Final)
Автор: Micah Lee
Издательство: No Starch Press
Год: 2024
Страниц: 544
Язык: английский
Формат: epub (true)
Размер: 15.3 MB

Unlock the internet’s treasure trove of public interest data with Hacks, Leaks, and Revelations by Micah Lee, an investigative reporter and security engineer. This hands-on guide blends real-world techniques for researching large datasets with lessons on coding, data authentication, and digital security. All of this is spiced up with gripping stories from the front lines of investigative journalism. Using Python or other programming languages, you can give your computer precise instructions for performing tasks that existing tools or shell scripts don’t allow. For example, you could write a Python script that scours a million pieces of video metadata to determine where the videos were filmed. In my experience, Python is also simpler, easier to understand, and less error-prone than shell scripts. This chapter provides a crash course on the fundamentals of Python programming. You’ll learn to write and execute Python scripts and use the interactive Python interpreter. You’ll also use Python to do math, define variables, work with strings and Boolean logic, loop through lists of items, and use functions. Future chapters rely on your understanding of these basic skills.

Название: Deep Learning For Physics Research
Автор: Martin Erdmann, Jonas Glombitza, Gregor Kasieczka, Uwe Klemradt
Издательство: World Scientific Publishing
Год: 2021
Страниц: 340
Язык: английский
Формат: pdf (true)
Размер: 18,4 MB

A core principle of physics is knowledge gained from data. Thus, Deep Learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what Deep Learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start Deep Learning. Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which Python code and training data can be downloaded.

Название: Statistics and Data Visualization in Climate Science with R and Python
Автор: Samuel S. P. Shen, Gerald R. North
Издательство: Cambridge University Press
Год: 2023
Страниц: 415
Язык: английский
Формат: pdf (true)
Размер: 35.5 MB

A comprehensive overview of essential statistical concepts, useful statistical methods, data visualization, and modern computing tools for the climate sciences and many others such as geography and environmental engineering. It is an invaluable reference for students and researchers in climatology and its connected fields who wish to learn data science, statistics, R and Python programming. The examples and exercises in the book empower readers to work on real climate data from station observations, remote sensing and simulated results. For example, students can use R or Python code to read and plot the global warming data and the global precipitation data in netCDF, csv, txt, or JSON; and compute and interpret empirical orthogonal functions. The book's computer code and real-world data allow readers to fully utilize the modern computing technology and updated datasets. Online supplementary resources include R code and Python code, data files, figure files, tutorials, slides and sample syllabi.

Название: Mastering OpenCV with Python: Use NumPy, Scikit, TensorFlow, and Matplotlib to learn Advanced algorithms for Machine Learning through a set of Practical Projects
Автор: Ayush Vaishya
Издательство: Orange Education Pvt Ltd, AVA
Год: November 2023
Страниц: 423
Язык: английский
Формат: epub (true)
Размер: 10.5 MB

Unlocking Visual Insights: OpenCV Made Simple and Powerful. "Mastering OpenCV with Python" immerses you in the captivating realm of computer vision, with a structured approach that equips you with the knowledge and skills essential for success in this rapidly evolving field. From grasping the fundamental concepts of image processing and OpenCV to mastering advanced techniques such as neural networks and object detection, you will gain a comprehensive understanding. Each chapter is enriched with hands-on exercises and real-world projects, ensuring the acquisition of practical skills that can be immediately applied in your professional journey. This book not only elevates your technical proficiency but also prepares you for a rewarding career. The technological job landscape is constantly evolving, and professionals who can harness the potential of computer vision are in high demand. This beginner-friendly book in computer vision requires no prior experience, making it accessible to newcomers. While a basic programming understanding is helpful, it's designed to guide individuals from diverse backgrounds into the captivating realms of AI, computer vision, and image processing.