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Building React Apps with Server-Side Rendering
Building React Apps with Server-Side Rendering

Leverage the benefits of both client-side and server-side rendering to get the most out of your React applications. By the end of this book you will be able to build and deploy React applications using the Next.js framework to fully render server-side HTML on every Web page. You'll begin by reviewing JavaScript fundamentals and how they work with the core principles of React. You'll then move on to Next.js, the React framework for server-rendered applications. Using this framework, you will create a fast and secure solutional React application that renders content on the server-side, protects sensitive information, and optimizes response times. Before deploying the application using Docker containers, you'll create automated unit tests to verify that every component is appropriately doing its job. Building React Apps with Server-Side Rendering also covers other fun and interesting topics such as Bootstrap 4, JSX (JavaScript XML), adding styling to your React applications, and muc ...
Graph Databases, 2nd Edition
Graph Databases, 2nd Edition

Discover how graph databases can help you manage and query highly connected data. With this practical book, you'll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. Learn how different organizations are using graph databases to outperform their competitors. With this book's data modeling, query, and code examples, you'll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model; Learn best practices and common pitfalls when modeling with graphs; Plan and implement a graph database solution in test-driven fashion ...
Natural Language Processing with Python and spaCy
Natural Language Processing with Python and spaCy

Natural Language Processing with Python and spaCy will show you how to create NLP applications like chatbots, text-condensing scripts, and order-processing tools quickly and easily. You'll learn how to leverage the spaCy library to extract meaning from text intelligently; how to determine the relationships between words in a sentence (syntactic dependency parsing); identify nouns, verbs, and other parts of speech (part-of-speech tagging); and sort proper nouns into categories like people, organizations, and locations (named entity recognizing). You'll even learn how to transform statements into questions to keep a conversation going. You'll also learn how to: Work with word vectors to mathematically find words with similar meanings; Identify patterns within data using spaCy's built-in displaCy visualizer; Automatically extract keywords from user input and store them in a relational database; Deploy a chatbot app to interact with users over the internet. ...
Python One-Liners
Python One-Liners

Python One-Liners will teach you how to read and write "one-liners": concise statements of useful functionality packed into a single line of code. You'll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert. The book's five chapters cover tips and tricks, regular expressions, machine learning, core data science topics, and useful algorithms. Detailed explanations of one-liners introduce key computer science concepts and boost your coding and analytical skills. You'll learn about advanced Python features such as list comprehension, slicing, lambda functions, regular expressions, map and reduce functions, and slice assignments. You'll also learn how to: Leverage data structures to solve real-world problems, like using Boolean indexing to find cities with above-average pollution; Use NumPy basics such as array, shape, axis, type, broadcasting, advanced indexing, slicing, sorting, searching, aggr ...
Hands-On Microservices with C# 8 and .NET Core 3, 3rd Edition
Hands-On Microservices with C# 8 and .NET Core 3, 3rd Edition

The microservice architectural style promotes the development of complex applications as a suite of small services based on specific business capabilities. With this book, you'll take a hands-on approach to build microservices and deploy them using ASP .NET Core and Microsoft Azure. You'll start by understanding the concept of microservices and their fundamental characteristics. This microservices book will then introduce a real-world app built as a monolith, currently struggling under increased demand and complexity, and guide you in its transition to microservices using the latest features of C# 8 and .NET Core 3. You'll identify service boundaries, split the application into multiple microservices, and define service contracts. You'll also explore how to configure, deploy, and monitor microservices using Docker and Kubernetes, and implement autoscaling in a microservices architecture for enhanced productivity. Once you've got to grips with reactive microservices, you'll discover ...
MicroPython Projects
MicroPython Projects

With the increasing complexity of embedded systems seen over the past few years, developers are looking for ways to manage them easily by solving problems without spending a lot of time on finding supported peripherals. MicroPython is an efficient and lean implementation of the Python 3 programming language, which is optimized to run on microcontrollers. MicroPython Projects will guide you in building and managing your embedded systems with ease. This book is a comprehensive project-based guide that will help you build a wide range of projects and give you the confidence to design complex projects spanning new areas of technology such as electronic applications, automation devices, and IoT applications. While building seven engaging projects, you'll learn how to enable devices to communicate with each other, access and control devices over a TCP/IP socket, and store and retrieve data. The complexity will increase progressively as you work on different projects, covering areas such a ...
Build a Career in Data Science
Build a Career in Data Science

You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. What are the keys to a data scientist's long-term success? Blending your technical know-how with the right "soft skills" turns out to be a central ingredient of a rewarding career. Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you'll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You'll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the bo ...
Succeeding with AI
Succeeding with AI

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 ensure they're cost effective and focused on the right business goals. Succeeding with AI requires talent, tools, and money. So why do many well-funded, state-of-the-art projects fail to deliver meaningful business value? Because talent, tools, and money aren't enough: You also need to know how to ask the right questions. In this unique book, AI consultant Veljko Krunic reveals a tested process to start AI projects right, so you'll get the results you want. Succeeding with AI sets out a framework for pl ...
Machine Learning with R, the tidyverse, and mlr
Machine Learning with R, the tidyverse, and mlr

Machine learning (ML) is a collection of programming techniques for discovering relationships in data. With ML algorithms, you can cluster and classify data for tasks like making recommendations or fraud detection and make predictions for sales trends, risk analysis, and other forecasts. Once the domain of academic data scientists, machine learning has become a mainstream business process, and tools like the easy-to-learn R programming language put high-quality data analysis in the hands of any programmer. Machine Learning with R, the tidyverse, and mlr teaches you widely used ML techniques and how to apply them to your own datasets using the R programming language and its powerful ecosystem of tools. This book will get you started! Machine Learning with R, the tidyverse, and mlr gets you started in machine learning using R Studio and the awesome mlr machine learning package. This practical guide simplifies theory and avoids needlessly complicated statistics or math. All core ML tec ...
Deep Reinforcement Learning in Action
Deep Reinforcement Learning in Action

Humans learn best from feedback - we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you'll need to implement it into your own projects. Deep reinforcement learning AI systems rapidly adapt to new environments, a vast improvement over standard neural networks. A DRL agent learns like people do, taking in raw data such as sensor input and refining its responses and predictions through trial and error. Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you'll master foundational and ...
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