Mostrando resultados por Editor "Manning Publications" en Todas las categorías

Getting MEAN with Mongo, Express, Angular, and Node teaches you how to develop web applications using the MEAN stack.

Centralized data warehouses, the long-time de facto standard for housing data for analytics, are rapidly giving way to multi-faceted cloud data platforms. Companies that embrace modern cloud data platforms benefit from an integrated view of their business using all of their data and can take advantage of advanced analytic practices to drive predictions and as yet unimagined data services.

Take the next steps in your data science career! This friendly and hands-on guide shows you how to start mastering Pandas with skills you already know from spreadsheet software.

Spring Microservices in Action: Second Edition teaches you to build microservice-based applications using Java and Spring. By dividing large applications into separate self-contained units, microservices are a great step toward reducing complexity and increasing flexibility. This second edition is fully updated for the latest version of Spring, with expanded coverage of API routing with Spring Cloud Gateway, logging with the ELK stack, metrics with Prometheus and Grafana, security with the Hashicorp Vault, and modern deployment practices with Kubernetes and Istio.

Objects are the central concept of languages like Java, Python, and C#. Applying the best practices for object design means that your code will be easy to read, write, and maintain. Object Design Style Guide captures dozens of techniques for creating pro-quality OO code that can stand the test of time.

The best way to learn microservices development is to build something! Bootstrapping Microservices with Docker, Kubernetes, and Terraform guides you from zero through to a complete microservices project, including fast prototyping, development, and deployment. You’ll get your feet wet using industry-standard tools as you learn and practice the practical skills you’ll use for every microservices application.

Professional developers know the many benefits of writing application code that’s clean, well-organized, and easy to maintain. By learning and following established patterns and best practices, you can take your code and your career to a new level. With Practices of the Python Pro, you’ll learn to design professional-level, clean, easily maintainable software at scale using the incredibly popular programming language, Python.

GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. In this book, you'll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and discriminator networks.

Algorithms of the Intelligent Web, Second Edition teaches you how to create machine learning applications that crunch and wrangle data collected from users, web applications, and website logs. In this totally revised edition, you'll look at intelligent algorithms that extract real value from data. Key machine learning concepts are explained with code examples in Python's scikit-learn. This book guides you through algorithms to capture, store, and structure data streams coming from the web.

This revision of Manning's popular The Quick Python Book offers a clear, crisp introduction to the elegant Python programming language and its famously easy-to-read syntax. Written for programmers new to Python, this edition covers features common to other languages concisely, while introducing Python's comprehensive standard functions library and unique features in detail. After exploring Python's syntax, control flow, and basic data structures, the book shows how to create, test, and deploy full applications and larger code libraries.

Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems.

Spring in Action, Fourth Edition is a hands-on guide to the Spring Framework, updated for version 4. It covers the features, tools, and practices including Spring MVC, REST, Security, Web Flow, and more. You'll move between short snippets and an ongoing example as you learn to build simple and efficient J2EE applications. Author Craig Walls has a special knack for crisp and entertaining examples that zoom in on the features and techniques you really need.

Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patterns and Practices you will learn: Internal functioning of modern convolutional neural networks, procedural reuse design pattern for CNN architectures, models for mobile and IoT devices, assembling large-scale model deployments, optimizing hyperparameter tuning, and migrating a model to a production environment.

In Learn Kubernetes in a Month of Lunches, you'll go from "what’s a Pod?" to automatically scaling clusters of containers and components in just 22 hands-on lessons, each short enough to fit into a lunch break. Every lesson is task-focused and covers an essential skill on the road to Kubernetes mastery. You'll learn how to smooth container management with Kubernetes, including securing your clusters, and upgrades and rollbacks with zero downtime.

Cloud Native Patterns is your guide to developing strong applications that thrive in the dynamic, distributed, virtual world of the cloud. This audiobook presents a mental model for cloud-native applications, along with the patterns, practices, and tooling that set them apart. Cloud platforms promise the holy grail: Near-zero downtime, infinite scalability, short feedback cycles, fault-tolerance, and cost control. But how do you get there? Learn these fundamental patterns and practices, and you’ll be ready to thrive in the dynamic, distributed, virtual world of the cloud.

Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Succeeding with AI sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It’s filled with practical techniques for running data science programs that are cost effective and focused on the right business goals.

JavaScript Application Design: A Build First Approach introduces JavaScript developers to techniques that will improve the quality of their software as well as their web development workflow. You'll begin by learning how to establish build processes that are appropriate for JavaScript-driven development. Then, you'll walk through best practices for productive day-to-day development, like running tasks when your code changes, deploying applications with a single command, and monitoring the state of your application once it's in production.

The only way to master a skill is to practice. In Python Workout, author Reuven M. Lerner guides you through 50 carefully selected exercises that invite you to flex your programming muscles. As you take on each new challenge, you'll build programming skill and confidence. The thorough explanations help you lock in what you've learned and apply it to your own projects.

Big data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades.

Serious developers know that code can always be improved. With each iteration, you make optimizations - small and large - that can have a huge impact on your application’s speed, size, resilience, and maintainability. In Seriously Good Software: Code That Works, Survives, and Wins, author, teacher, and Java expert Marco Faella teaches you techniques for writing better code. You’ll start with a simple application and follow it through seven careful refactorings, each designed to explore another dimension of quality.