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

Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You’ll explore interesting real-world datasets like Google’s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.

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.

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.

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.

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.

Start thinking about your development pipeline as a mission-critical application. Pipeline as Code is a practical guide to automating your development pipeline in a cloud-native, service-driven world. You’ll use the latest infrastructure-as-code tools like Packer and Terraform to develop reliable CI/CD pipelines for numerous cloud-native applications. Treat your CI/CD pipeline like the real application it is. With the Pipeline as Code approach, you create a collection of scripts that replace the tedious web UI wrapped around most CI/CD systems.

Every new version of Java is important, but Java 8 was a game changer. Java 8 in Action is a clearly written guide to the new features of Java 8. It begins with a practical introduction to lambdas, using real-world Java code. Next, it covers the new Streams API and shows how you can use it to make collection-based code radically easier to understand and maintain.

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

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.

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.

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.

The Art of Unit Testing, Second Edition guides you step-by-step from writing your first simple tests to developing robust test sets that are maintainable, readable, and trustworthy. You'll master the foundational ideas and quickly move to high-value subjects like mocks, stubs, and isolation, including frameworks such as Moq, FakeItEasy, and Typemock Isolator.

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.

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.

Classic Computer Science Problems in Python sharpens your CS problem-solving skills with time-tested scenarios, exercises, and algorithms, using Python. You'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. You'll especially enjoy the feeling of satisfaction as you crack problems that connect computer science to the real-world concerns of apps, data, performance, and even nailing your next job interview!

Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data.

Code performance versus simplicity. Delivery speed versus duplication. Flexibility versus maintainability—every decision you make in software engineering involves balancing tradeoffs. In Software Mistakes and Tradeoffs, you’ll learn from costly mistakes that Tomasz Lelek and Jon Skeet have encountered over their impressive careers. You’ll explore real-world scenarios where poor understanding of tradeoffs leads to major problems down the road, so you can preempt your own mistakes with a more thoughtful approach to decision-making.

Learn data science with Python by building five real-world projects! Experiment with card game predictions, tracking disease outbreaks, and more, as you build a flexible and intuitive understanding of data science. In Data Science Bookcamp, you’ll test and build your knowledge of Python with the kind of open-ended problems that professional data scientists work on every day. Downloadable data sets and thoroughly-explained solutions help you lock in what you’ve learned, building your confidence and making you ready for an exciting new data science career.

Get Programming: Learn to Code with Python introduces you to the world of writing computer programs without drowning you in confusing jargon or theory that make getting started harder than it should be. Filled with practical examples and step-by-step lessons using the easy-on-the-brain Python language, this book will get you programming in no time!

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.