Programowanie
Stefanie Molin
Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value.Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data.By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets.
Roy Jafari
Hands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who’s developed college-level courses on data preprocessing and related subjects. With this book, you’ll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you’ll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data.By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools.
Yoon Hyup Hwang
Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies.This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R.By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business.
Yuxing Yan, James Yan
Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world.The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R.
Jason Morris, Chris McCubbin, Raymond Page
The Command Line has been in existence on UNIX-based OSes in the form of Bash shell for over 3 decades. However, very little is known to developers as to how command-line tools can be OSEMN (pronounced as awesome and standing for Obtaining, Scrubbing, Exploring, Modeling, and iNterpreting data) for carrying out simple-to-advanced data science tasks at speed.This book will start with the requisite concepts and installation steps for carrying out data science tasks using the command line. You will learn to create a data pipeline to solve the problem of working with small-to medium-sized files on a single machine. You will understand the power of the command line, learn how to edit files using a text-based and an. You will not only learn how to automate jobs and scripts, but also learn how to visualize data using the command line. By the end of this book, you will learn how to speed up the process and perform automated tasks using command-line tools.
Chandra Sekhar Nayak, Rivu Chakraborty
Data structures and algorithms are more than just theoretical concepts. They help you become familiar with computational methods for solving problems and writing logical code. Equipped with this knowledge, you can write efficient programs that run faster and use less memory.Hands-On Data Structures and Algorithms with Kotlin book starts with the basics of algorithms and data structures, helping you get to grips with the fundamentals and measure complexity. You'll then move on to exploring the basics of functional programming while getting used to thinking recursively. Packed with plenty of examples along the way, this book will help you grasp each concept easily. In addition to this, you'll get a clear understanding of how the data structures in Kotlin's collection framework work internally.By the end of this book, you will be able to apply the theory of data structures and algorithms to work out real-world problems.
Dr. Basant Agarwal
Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You’ll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer.By the end of this Python book, you’ll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.
Dr. Basant Agarwal, Benjamin Baka
Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.
Dr. Basant Agarwal, Benjamin Baka
Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.
Claus Matzinger
Rust has come a long way and is now utilized in several contexts. Its key strengths are its software infrastructure and resource-constrained applications, including desktop applications, servers, and performance-critical applications, not forgetting its importance in systems' programming. This book will be your guide as it takes you through implementing classic data structures and algorithms in Rust, helping you to get up and running as a confident Rust programmer. The book begins with an introduction to Rust data structures and algorithms, while also covering essential language constructs. You will learn how to store data using linked lists, arrays, stacks, and queues. You will also learn how to implement sorting and searching algorithms. You will learn how to attain high performance by implementing algorithms to string data types and implement hash structures in algorithm design. The book will examine algorithm analysis, including Brute Force algorithms, Greedy algorithms, Divide and Conquer algorithms, Dynamic Programming, and Backtracking. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications.
Claus Matzinger
Rust has come a long way and is now utilized in several contexts. Its key strengths are its software infrastructure and resource-constrained applications, including desktop applications, servers, and performance-critical applications, not forgetting its importance in systems' programming. This book will be your guide as it takes you through implementing classic data structures and algorithms in Rust, helping you to get up and running as a confident Rust programmer. The book begins with an introduction to Rust data structures and algorithms, while also covering essential language constructs. You will learn how to store data using linked lists, arrays, stacks, and queues. You will also learn how to implement sorting and searching algorithms. You will learn how to attain high performance by implementing algorithms to string data types and implement hash structures in algorithm design. The book will examine algorithm analysis, including Brute Force algorithms, Greedy algorithms, Divide and Conquer algorithms, Dynamic Programming, and Backtracking. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications.
Claus Matzinger
Rust has come a long way and is now utilized in several contexts. Its key strengths are its software infrastructure and resource-constrained applications, including desktop applications, servers, and performance-critical applications, not forgetting its importance in systems' programming. This book will be your guide as it takes you through implementing classic data structures and algorithms in Rust, helping you to get up and running as a confident Rust programmer. The book begins with an introduction to Rust data structures and algorithms, while also covering essential language constructs. You will learn how to store data using linked lists, arrays, stacks, and queues. You will also learn how to implement sorting and searching algorithms. You will learn how to attain high performance by implementing algorithms to string data types and implement hash structures in algorithm design. The book will examine algorithm analysis, including Brute Force algorithms, Greedy algorithms, Divide and Conquer algorithms, Dynamic Programming, and Backtracking. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications.
Claus Matzinger
Rust has come a long way and is now utilized in several contexts. Its key strengths are its software infrastructure and resource-constrained applications, including desktop applications, servers, and performance-critical applications, not forgetting its importance in systems' programming. This book will be your guide as it takes you through implementing classic data structures and algorithms in Rust, helping you to get up and running as a confident Rust programmer. The book begins with an introduction to Rust data structures and algorithms, while also covering essential language constructs. You will learn how to store data using linked lists, arrays, stacks, and queues. You will also learn how to implement sorting and searching algorithms. You will learn how to attain high performance by implementing algorithms to string data types and implement hash structures in algorithm design. The book will examine algorithm analysis, including Brute Force algorithms, Greedy algorithms, Divide and Conquer algorithms, Dynamic Programming, and Backtracking. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications.
Hands-On Data Visualization with Bokeh. Interactive web plotting for Python using Bokeh
Kevin Jolly
Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free. This book gets you up to speed with Bokeh - a popular Python library for interactive data visualization.The book starts out by helping you understand how Bokeh works internally and how you can set up and install the package in your local machine. You then use a real world data set which uses stock data from Kaggle to create interactive and visually stunning plots. You will also learn how to leverage Bokeh using some advanced concepts such as plotting with spatial and geo data. Finally you will use all the concepts that you have learned in the previous chapters to create your very own Bokeh application from scratch.By the end of the book you will be able to create your very own Bokeh application. You will have gone through a step by step process that starts with understanding what Bokeh actually is and ends with building your very own Bokeh application filled with interactive and visually aesthetic plots.
Sudharsan Ravichandiran
Deep learning is one of the most popular domains in the AI space that allows you to develop multi-layered models of varying complexities. This book introduces you to popular deep learning algorithms—from basic to advanced—and shows you how to implement them from scratch using TensorFlow. Throughout the book, you will gain insights into each algorithm, the mathematical principles involved, and how to implement it in the best possible manner. The book starts by explaining how you can build your own neural networks, followed by introducing you to TensorFlow, the powerful Python-based library for machine learning and deep learning. Moving on, you will get up to speed with gradient descent variants, such as NAG, AMSGrad, AdaDelta, Adam, and Nadam. The book will then provide you with insights into recurrent neural networks (RNNs) and LSTM and how to generate song lyrics with RNN. Next, you will master the math necessary to work with convolutional and capsule networks, widely used for image recognition tasks. You will also learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Finally, you will explore GANs, including InfoGAN and LSGAN, and autoencoders, such as contractive autoencoders and VAE. By the end of this book, you will be equipped with all the skills you need to implement deep learning in your own projects.
Yuxi (Hayden) Liu, Saransh Mehta
Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and implement deep learning architectures to resolve various deep learning research problems.Hands-On Deep Learning Architectures with Python explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations and ideas to help you build efficient artificial intelligence systems (AI), this book will help you learn how neural networks play a major role in building deep architectures. You will understand various deep learning architectures (such as AlexNet, VGG Net, GoogleNet) with easy-to-follow code and diagrams. In addition to this, the book will also guide you in building and training various deep architectures such as the Boltzmann mechanism, autoencoders, convolutional neural networks (CNNs), recurrent neural networks (RNNs), natural language processing (NLP), GAN, and more—all with practical implementations.By the end of this book, you will be able to construct deep models using popular frameworks and datasets with the required design patterns for each architecture. You will be ready to explore the potential of deep architectures in today's world.
Micheal Lanham
The number of applications of deep learning and neural networks has multiplied in the last couple of years. Neural nets has enabled significant breakthroughs in everything from computer vision, voice generation, voice recognition and self-driving cars. Game development is also a key area where these techniques are being applied. This book will give an in depth view of the potential of deep learning and neural networks in game development. We will take a look at the foundations of multi-layer perceptron’s to using convolutional and recurrent networks. In applications from GANs that create music or textures to self-driving cars and chatbots. Then we introduce deep reinforcement learning through the multi-armed bandit problem and other OpenAI Gym environments.As we progress through the book we will gain insights about DRL techniques such as Motivated Reinforcement Learning with Curiosity and Curriculum Learning. We also take a closer look at deep reinforcement learning and in particular the Unity ML-Agents toolkit. By the end of the book, we will look at how to apply DRL and the ML-Agents toolkit to enhance, test and automate your games or simulations. Finally, we will cover your possible next steps and possible areas for future learning.
Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications
Dr. Mohammad Abdur Razzaque , Md. Rezaul...
Artificial Intelligence is growing quickly, which is driven by advancements in neural networks(NN) and deep learning (DL). With an increase in investments in smart cities, smart healthcare, and industrial Internet of Things (IoT), commercialization of IoT will soon be at peak in which massive amounts of data generated by IoT devices need to be processed at scale. Hands-On Deep Learning for IoT will provide deeper insights into IoT data, which will start by introducing how DL fits into the context of making IoT applications smarter. It then covers how to build deep architectures using TensorFlow, Keras, and Chainer for IoT. You’ll learn how to train convolutional neural networks(CNN) to develop applications for image-based road faults detection and smart garbage separation, followed by implementing voice-initiated smart light control and home access mechanisms powered by recurrent neural networks(RNN). You’ll master IoT applications for indoor localization, predictive maintenance, and locating equipment in a large hospital using autoencoders, DeepFi, and LSTM networks. Furthermore, you’ll learn IoT application development for healthcare with IoT security enhanced. By the end of this book, you will have sufficient knowledge need to use deep learning efficiently to power your IoT-based applications for smarter decision making.
Guglielmo Iozzia
Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark.The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark.As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models.By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases.
Corey Scott
Hands-On Dependency Injection in Go takes you on a journey, teaching you about refactoring existing code to adopt dependency injection (DI) using various methods available in Go.Of the six methods introduced in this book, some are conventional, such as constructor or method injection, and some unconventional, such as just-in-time or config injection. Each method is explained in detail, focusing on their strengths and weaknesses, and is followed with a step-by-step example of how to apply it. With plenty of examples, you will learn how to leverage DI to transform code into something simple and flexible. You will also discover how to generate and leverage the dependency graph to spot and eliminate issues. Throughout the book, you will learn to leverage DI in combination with test stubs and mocks to test otherwise tricky or impossible scenarios.Hands-On Dependency Injection in Go takes a pragmatic approach and focuses heavily on the code, user experience, and how to achieve long-term benefits through incremental changes.By the end of this book, you will have produced clean code that’s easy to test.
Corey Scott
Hands-On Dependency Injection in Go takes you on a journey, teaching you about refactoring existing code to adopt dependency injection (DI) using various methods available in Go.Of the six methods introduced in this book, some are conventional, such as constructor or method injection, and some unconventional, such as just-in-time or config injection. Each method is explained in detail, focusing on their strengths and weaknesses, and is followed with a step-by-step example of how to apply it. With plenty of examples, you will learn how to leverage DI to transform code into something simple and flexible. You will also discover how to generate and leverage the dependency graph to spot and eliminate issues. Throughout the book, you will learn to leverage DI in combination with test stubs and mocks to test otherwise tricky or impossible scenarios.Hands-On Dependency Injection in Go takes a pragmatic approach and focuses heavily on the code, user experience, and how to achieve long-term benefits through incremental changes.By the end of this book, you will have produced clean code that’s easy to test.
Tom Kwong
Design patterns are fundamental techniques for developing reusable and maintainable code. They provide a set of proven solutions that allow developers to solve problems in software development quickly. This book will demonstrate how to leverage design patterns with real-world applications.Starting with an overview of design patterns and best practices in application design, you'll learn about some of the most fundamental Julia features such as modules, data types, functions/interfaces, and metaprogramming. You'll then get to grips with the modern Julia design patterns for building large-scale applications with a focus on performance, reusability, robustness, and maintainability. The book also covers anti-patterns and how to avoid common mistakes and pitfalls in development. You'll see how traditional object-oriented patterns can be implemented differently and more effectively in Julia. Finally, you'll explore various use cases and examples, such as how expert Julia developers use design patterns in their open source packages.By the end of this Julia programming book, you'll have learned methods to improve software design, extensibility, and reusability, and be able to use design patterns efficiently to overcome common challenges in software development.
Gaurav Aroraa, Jeffrey Chilberto
Design patterns are essentially reusable solutions to common programming problems. When used correctly, they meet crucial software requirements with ease and reduce costs. This book will uncover effective ways to use design patterns and demonstrate their implementation with executable code specific to both C# and .NET Core.Hands-On Design Patterns with C# and .NET Core begins with an overview of object-oriented programming (OOP) and SOLID principles. It provides an in-depth explanation of the Gang of Four (GoF) design patterns, including creational, structural, and behavioral. The book then takes you through functional, reactive, and concurrent patterns, helping you write better code with streams, threads, and coroutines. Toward the end of the book, you’ll learn about the latest trends in architecture, exploring design patterns for microservices, serverless, and cloud native applications. You’ll even understand the considerations that need to be taken into account when choosing between different architectures such as microservices and MVC.By the end of the book, you will be able to write efficient and clear code and be comfortable working on scalable and maintainable projects of any size.
Gaurav Aroraa, Jeffrey Chilberto
Design patterns are essentially reusable solutions to common programming problems. When used correctly, they meet crucial software requirements with ease and reduce costs. This book will uncover effective ways to use design patterns and demonstrate their implementation with executable code specific to both C# and .NET Core.Hands-On Design Patterns with C# and .NET Core begins with an overview of object-oriented programming (OOP) and SOLID principles. It provides an in-depth explanation of the Gang of Four (GoF) design patterns, including creational, structural, and behavioral. The book then takes you through functional, reactive, and concurrent patterns, helping you write better code with streams, threads, and coroutines. Toward the end of the book, you’ll learn about the latest trends in architecture, exploring design patterns for microservices, serverless, and cloud native applications. You’ll even understand the considerations that need to be taken into account when choosing between different architectures such as microservices and MVC.By the end of the book, you will be able to write efficient and clear code and be comfortable working on scalable and maintainable projects of any size.
Fedor G. Pikus
C++ is a general-purpose programming language designed with the goals of efficiency, performance, and flexibility in mind. Design patterns are commonly accepted solutions to well-recognized design problems. In essence, they are a library of reusable components, only for software architecture, and not for a concrete implementation.The focus of this book is on the design patterns that naturally lend themselves to the needs of a C++ programmer, and on the patterns that uniquely benefit from the features of C++, in particular, the generic programming. Armed with the knowledge of these patterns, you will spend less time searching for a solution to a common problem and be familiar with the solutions developed from experience, as well as their advantages and drawbacks. The other use of design patterns is as a concise and an efficient way to communicate. A pattern is a familiar and instantly recognizable solution to specific problem; through its use, sometimes with a single line of code, we can convey a considerable amount of information. The code conveys: This is the problem we are facing, these are additional considerations that are most important in our case; hence, the following well-known solution was chosen.By the end of this book, you will have gained a comprehensive understanding of design patterns to create robust, reusable, and maintainable code.
Fedor G. Pikus
C++ is a general-purpose programming language designed for efficiency, performance, and flexibility. Design patterns are commonly accepted solutions to well-recognized design problems. In essence, they are a library of reusable components, only for software architecture, and not for a concrete implementation. This book helps you focus on the design patterns that naturally adapt to your needs, and on the patterns that uniquely benefit from the features of C++. Armed with the knowledge of these patterns, you’ll spend less time searching for solutions to common problems and tackle challenges with the solutions developed from experience. You’ll also explore that design patterns are a concise and efficient way to communicate, as patterns are a familiar and recognizable solution to a specific problem and can convey a considerable amount of information with a single line of code. By the end of this book, you’ll have a deep understanding of how to use design patterns to write maintainable, robust, and reusable software.
Primož Gabrijelčič
Design patterns have proven to be the go-to solution for many common programming scenarios. This book focuses on design patterns applied to the Delphi language. The book will provide you with insights into the language and its capabilities of a runtime library.You'll start by exploring a variety of design patterns and understanding them through real-world examples. This will entail a short explanation of the concept of design patterns and the original set of the 'Gang of Four' patterns, which will help you in structuring your designs efficiently. Next, you'll cover the most important 'anti-patterns' (essentially bad software development practices) to aid you in steering clear of problems during programming. You'll then learn about the eight most important patterns for each creational, structural, and behavioral type. After this, you'll be introduced to the concept of 'concurrency' patterns, which are design patterns specifically related to multithreading and parallel computation. These will enable you to develop and improve an interface between items and harmonize shared memories within threads. Toward the concluding chapters, you'll explore design patterns specific to program design and other categories of patterns that do not fall under the 'design' umbrella.By the end of this book, you'll be able to address common design problems encountered while developing applications and feel confident while building scalable projects.
Dr. Edward Lavieri Jr.
Java design patterns are reusable and proven solutions to software design problems. This book covers over 60 battle-tested design patterns used by developers to create functional, reusable, and flexible software. Hands-On Design Patterns with Java starts with an introduction to the Unified Modeling Language (UML), and delves into class and object diagrams with the help of detailed examples. You'll study concepts and approaches to object-oriented programming (OOP) and OOP design patterns to build robust applications. As you advance, you'll explore the categories of GOF design patterns, such as behavioral, creational, and structural, that help you improve code readability and enable large-scale reuse of software. You’ll also discover how to work effectively with microservices and serverless architectures by using cloud design patterns, each of which is thoroughly explained and accompanied by real-world programming solutions. By the end of the book, you’ll be able to speed up your software development process using the right design patterns, and you’ll be comfortable working on scalable and maintainable projects of any size.
Alexey Soshin
Design patterns enable you as a developer to speed up the development process by providing you with proven development paradigms. Reusing design patterns helps prevent complex issues that can cause major problems, improves your code base, promotes code reuse, and makes an architecture more robust.The mission of this book is to ease the adoption of design patterns in Kotlin and provide good practices for programmers. The book begins by showing you the practical aspects of smarter coding in Kotlin, explaining the basic Kotlin syntax and the impact of design patterns. From there, the book provides an in-depth explanation of the classical design patterns of creational, structural, and behavioral families, before heading into functional programming. It then takes you through reactive and concurrent patterns, teaching you about using streams, threads, and coroutines to write better code along the way By the end of the book, you will be able to efficiently address common problems faced while developing applications and be comfortable working on scalable and maintainable projects of any size.
Mateusz Grzesiukiewicz
React Native helps developers reuse code across different mobile platforms like iOS and Android.This book will show you effective design patterns in the React Native world and will make you ready for professional development in big teams.The book will focus only on the patterns that are relevant to JavaScript, ECMAScript, React and React Native. However, you can successfully transfer a lot of the skills and techniques to other languages. I call them “Idea patterns”.This book will start with the most standard development patterns in React like component building patterns, styling patterns in React Native and then extend these patterns to your mobile application using real world practical examples. Each chapter comes with full, separate source code of applications that you can build and run on your phone.The book is also diving into architectural patterns. Especially how to adapt MVC to React environment. You will learn Flux architecture and how Redux is implementing it. Each approach will be presented with its pros and cons. You will learn how to work with external data sources using libraries like Redux thunk and Redux Saga.The end goal is the ability to recognize the best solution for a given problem for your next mobile application.