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Hands Down, Speak Out: Listening and Talking Across Literacy and Math
by Kassia Omohundro Wedekind Christy Hermann ThompsonFew skills are as critical or as rare today as the ability to hear and comprehend what other people are saying. The authors of' Hands Down, Speak Out' argue that we need new tools to teach the art of listening and they' ve put forward a simple yet transformative model for encouraging student conversations that are inclusive, empowering, and rich in content. This classroom guide for grades K-5 is particularly needed in the aftermath of two disrupted school years.' ' Teaching Foundational Skills Across Subjects:' Hands Down, Speak Out' is a practical guide for teaching listening and talking skills that span both literacy and math instruction and can be applied to a multitude of curriculums. K-5 Classroom Management Focused on Dialogue: Too often, the practice of hand-raising favors the performance of answers by a few students over the construction of meaning involving the whole class. Help' all' students develop dialogue skills that will deepen their understanding of literacy and mathematics, as well as of themselves, their communities, and the world. 28 Student-Centered Micro Lessons: Each of these short, incremental lessons build specific skills during content instruction rather than taking time away from it. Students will be energized by a discourse structure in which their ideas and voices take the lead while teachers focus on listening and facilitating. Nurturing Disagreements: The authors' provide guidance for managing difficult conversations by teaching students to engage in debate and discussion in a way that values listening equally with talking. Students are able to spend time developing active listening and speaking skills in a constructive environment. When we build talk communities with children, our greatest hope is that what they learn through talking about reading, writing, and math is matched by what they learn about living in the world with others, write Kassia Omohundro Wedekind and Christy Hermann Thompson.' Hands Down, Speak Out' demonstrates how teachers and leaders can run inclusive and accessible classrooms that respect each student' s level of participation.
Hands-On Data Science for Librarians (Chapman & Hall/CRC Data Science Series)
by Sarah Lin Dorris ScottLibrarians understand the need to store, use and analyze data related to their collection, patrons and institution, and there has been consistent interest over the last 10 years to improve data management, analysis, and visualization skills within the profession. However, librarians find it difficult to move from out-of-the-box proprietary software applications to the skills necessary to perform the range of data science actions in code. This book will focus on teaching R through relevant examples and skills that librarians need in their day-to-day lives that includes visualizations but goes much further to include web scraping, working with maps, creating interactive reports, machine learning, and others. While there’s a place for theory, ethics, and statistical methods, librarians need a tool to help them acquire enough facility with R to utilize data science skills in their daily work, no matter what type of library they work at (academic, public or special). By walking through each skill and its application to library work before walking the reader through each line of code, this book will support librarians who want to apply data science in their daily work. Hands-On Data Science for Librarians is intended for librarians (and other information professionals) in any library type (public, academic or special) as well as graduate students in library and information science (LIS). Key Features: Only data science book available geared toward librarians that includes step-by-step code examples Examples include all library types (public, academic, special) Relevant datasets Accessible to non-technical professionals Focused on job skills and their applications
Hands-On Data Structures and Algorithms with Go: Level Up Your Go Programming Skills To Develop Faster And More Efficient Code
by Bhagvan KommadiThis comprehensive book is for developers who want to understand how to select the best data structures and algorithms that will help to solve specific problems. Basic Go programming knowledge would be an added advantage.
Hands-On Data Visualization: Interactive Storytelling From Spreadsheets To Code
by Jack Dougherty Ilya IlyankouTell your story and show it with data, using free and easy-to-learn tools on the web. This introductory book teaches you how to design interactive charts and customized maps for your website, beginning with simple drag-and-drop tools such as Google Sheets, Datawrapper, and Tableau Public. You'll also gradually learn how to edit open source code templates like Chart.js, Highcharts, and Leaflet on GitHub.Hands-On Data Visualization takes you step-by-step through tutorials, real-world examples, and online resources. This practical guide is ideal for students, nonprofit organizations, small business owners, local governments, journalists, academics, and anyone who wants to take data out of spreadsheets and turn it into lively interactive stories. No coding experience is required.Build interactive charts and maps and embed them in your websiteUnderstand the principles for designing effective charts and mapsLearn key data visualization concepts to help you choose the right toolsConvert and transform tabular and spatial data to tell your data storyEdit and host Chart.js, Highcharts, and Leaflet map code templates on GitHubLearn how to detect bias in charts and maps produced by others
Hands-on Deep Learning: A Guide to Deep Learning with Projects and Applications
by Harsh BhasinThis book discusses deep learning, from its fundamental principles to its practical applications, with hands-on exercises and coding. It focuses on deep learning techniques and shows how to apply them across a wide range of practical scenarios. The book begins with an introduction to the core concepts of deep learning. It delves into topics such as transfer learning, multi-task learning, and end-to-end learning, providing insights into various deep learning models and their real-world applications. Next, it covers neural networks, progressing from single-layer perceptrons to multi-layer perceptrons, and solving the complexities of backpropagation and gradient descent. It explains optimizing model performance through effective techniques, addressing key considerations such as hyperparameters, bias, variance, and data division. It also covers convolutional neural networks (CNNs) through two comprehensive chapters, covering the architecture, components, and significance of kernels implementing well-known CNN models such as AlexNet and LeNet. It concludes with exploring autoencoders and generative models such as Hopfield Networks and Boltzmann Machines, applying these techniques to a diverse set of practical applications. These applications include image classification, object detection, sentiment analysis, COVID-19 detection, and ChatGPT. By the end of this book, you will have gained a thorough understanding of deep learning, from its fundamental principles to its innovative applications, enabling you to apply this knowledge to solve a wide range of real-world problems. What You Will Learn What are deep neural networks? What is transfer learning, multi-task learning, and end-to-end learning? What are hyperparameters, bias, variance, and data division? What are CNN and RNN? Who This Book Is For Machine learning engineers, data scientists, AI practitioners, software developers, and engineers interested in deep learning
Hands-On Deep Learning Algorithms with Python: Master deep learning algorithms with extensive math by implementing them using TensorFlow
by Sudharsan RavichandiranUnderstand basic to advanced deep learning algorithms, the mathematical principles behind them, and their practical applications. Key Features Get up-to-speed with building your own neural networks from scratch Gain insights into the mathematical principles behind deep learning algorithms Implement popular deep learning algorithms such as CNNs, RNNs, and more using TensorFlow Book Description Deep learning is one of the most popular domains in the AI space, allowing 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 behind it, 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 RNNs and LSTM and how to generate song lyrics with RNN. Next, you will master the math for convolutional and capsule networks, widely used for image recognition tasks. Then you learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Afterward, you will explore various 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. What you will learn Implement basic-to-advanced deep learning algorithms Master the mathematics behind deep learning algorithms Become familiar with gradient descent and its variants, such as AMSGrad, AdaDelta, Adam, and Nadam Implement recurrent networks, such as RNN, LSTM, GRU, and seq2seq models Understand how machines interpret images using CNN and capsule networks Implement different types of generative adversarial network, such as CGAN, CycleGAN, and StackGAN Explore various types of autoencoder, such as Sparse autoencoders, DAE, CAE, and VAE Who this book is for If you are a machine learning engineer, data scientist, AI developer, or simply want to focus on neural networks and deep learning, this book is for you. Those who are completely new to deep learning, but have some experience in machine learning and Python programming, will also find the book very helpful.
Hands-On Embedded Programming with Qt: Develop high performance applications for embedded systems with C++ and Qt 5
by John WernerA comprehensive guide that will get you up and running with embedded software development using Qt5 Key Features Learn to create fluid, cross-platform applications for embedded devices Achieve optimum performance in your applications with QT Lite project Explore the implementation of Qt with IoT using QtMqtt, QtKNX, and QtWebSockets Book Description Qt is an open-source toolkit suitable for cross-platform and embedded application development. This book uses inductive teaching to help you learn how to create applications for embedded and Internet of Things (IoT) devices with Qt 5. You'll start by learning to develop your very first application with Qt. Next, you'll build on the first application by understanding new concepts through hands-on projects and written text. Each project will introduce new features that will help you transform your basic first project into a connected IoT application running on embedded hardware. In addition to practical experience in developing an embedded Qt project, you will also gain valuable insights into best practices for Qt development, along with exploring advanced techniques for testing, debugging, and monitoring the performance of Qt applications. Through the course of the book, the examples and projects are demonstrated in a way so that they can be run both locally and on an embedded platform. By the end of this book, you will have the skills you need to use Qt 5 to confidently develop modern embedded applications. What you will learn Understand how to develop Qt applications using Qt Creator under Linux Explore various Qt GUI technologies to build resourceful and interactive applications Understand Qt's threading model to maintain a responsive UI Get to grips with remote target load and debug under Qt Creator Become adept at writing IoT code using Qt Learn a variety of software best practices to ensure that your code is efficient Who this book is for This book is for software and hardware professionals with experience in different domains who are seeking new career opportunities in embedded systems and IoT. Working knowledge of the C++ Linux command line will be useful to get the most out of this book.
Hands-On Financial Trading with Python: A practical guide to using Zipline and other Python libraries for backtesting trading strategies
by Jiri Pik Sourav GhoshDiscover how to build and backtest algorithmic trading strategies with ZiplineKey FeaturesGet to grips with market data and stock analysis and visualize data to gain quality insightsFind out how to systematically approach quantitative research and strategy generation/backtesting in algorithmic tradingLearn how to navigate the different features in Python's data analysis librariesBook DescriptionAlgorithmic trading helps you stay ahead of the markets by devising strategies in quantitative analysis to gain profits and cut losses. The book starts by introducing you to algorithmic trading and explaining why Python is the best platform for developing trading strategies. You'll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources. Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. You'll also focus on time series forecasting, covering pmdarima and Facebook Prophet. By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization.What you will learnDiscover how quantitative analysis works by covering financial statistics and ARIMAUse core Python libraries to perform quantitative research and strategy development using real datasetsUnderstand how to access financial and economic data in PythonImplement effective data visualization with MatplotlibApply scientific computing and data visualization with popular Python librariesBuild and deploy backtesting algorithmic trading strategiesWho this book is forThis book is for data analysts and financial traders who want to explore how to design algorithmic trading strategies using Python's core libraries. If you are looking for a practical guide to backtesting algorithmic trading strategies and building your own strategies, then this book is for you. Beginner-level working knowledge of Python programming and statistics will be helpful.
Hands-On Functional Programming with C++: An effective guide to writing accelerated functional code using C++17 and C++20
by Alexandru Bolboaca<p>Learn functional programming and build robust applications using the latest functional features in C++ <p>Key Features: <p> <li>Learn programming concepts such as loops, expressive code, and simple parallelization <li>Understand the working of Lambdas and Currying and write Pure functions <li>Explore event sourcing and other functional patterns to improve the efficiency of your applications</li> <p>Functional programming enables you to divide your software into smaller, reusable components that are easy to write, debug, and maintain. Combined with the power of C++, you can develop scalable and functional applications for modern software requirements. This book will help you discover the functional features in C++ 17 and C++ 20 to build enterprise-level applications. <p>Starting with the fundamental building blocks of functional programming and how to use them in C++, you'll explore functions, currying, and lambdas. As you advance, you'll learn how to improve cohesion and delve into test-driven development, which will enable you in designing better software. In addition to this, the book covers architectural patterns such as event sourcing to help you get to grips with the importance of immutability for data storage. You'll even understand how to “think in functions” and implement design patterns in a functional way. <p>By the end of this book, you'll be able to write faster and cleaner production code in C++ with the help of functional programming. <p>What you will learn: <p> <li>Understand the fundamentals of functional programming <li>Structure your code by understanding the building blocks of functional programming <li>Compare design styles in functional programming and object-oriented programming (OOP) <li>Use the concept of currying to create new functions in C++ <li>Become skilled at implementing design patterns in a functional way <li>Get to grips with multithreading by means of functional programming <li>Learn how to improve memory consumption when using functional constructs </li> <p>Who this book is for: This book is for C++ developers who want to learn functional programming but have little to no knowledge of the paradigm. Although no prior knowledge of functional programming is necessary, basic C++ programming experience will help you understand key concepts covered in the book.</p>
Hands-On Geometry: Constructions With a Straightedge and Compass (Grades 4-6)
by Christopher M. FreemanPut compasses into your students' hands and behold the results! Hands-On Geometry teaches students to draw accurate constructions of equilateral triangles, squares, and regular hexagons, octagons, and dodecagons; to construct kites and use their diagonals to construct altitudes, angle bisectors, perpendicular bisectors, and the inscribed and circumscribed circles of any triangle; to construct perpendicular lines and rectangles, parallel lines, and parallelograms; and to construct a regular pentagon and a golden rectangle.Students will enjoy fulfilling high standards of precision with these hands-on activities. Hands-On Geometry provides the background students need to become exceptionally well prepared for a formal geometry class. The book provides an easy way to differentiate instruction: Because the lessons are self-explanatory, students can proceed at their own pace, and the finished constructions can be assessed at a glance.Grades 4-6
Hands-On Gradient Boosting with XGBoost and scikit-learn: Perform Accessible Machine Learning And Extreme Gradient Boosting With Python
by Corey WadeThis book is for data science professionals and enthusiasts, data analysts, and developers who want to build fast and accurate machine learning models that scale with big data. Proficiency in Python and a basic understanding of linear algebra will help you to get the most out of this book.
Hands-On High performance with QT: Build cross-platform applications using concurrency, parallel programming, and memory management
by Marek KrajewskiThis book for Qt developers who wish to build highly performant applications for desktop and embedded devices, and have C++ knowledge.
A Hands-on Introduction to Big Data Analytics
by Funmi Obembe Ofer EngelThis practical textbook offers a hands-on introduction to big data analytics, helping you to develop the skills required to hit the ground running as a data professional. It complements theoretical foundations with an emphasis on the application of big data analytics, illustrated by real-life examples and datasets. Containing comprehensive coverage of all the key topics in this area, this book uses open-source technologies and examples in Python and Apache Spark. Learning features include: - Ethics by Design encourages you to consider data ethics at every stage. - Industry Insights facilitate a deeper understanding of the link between what you are studying and how it is applied in industry. - Datasets, questions, and exercises give you the opportunity to apply your learning. Dr Funmi Obembe is the Head of Technology at the Faculty of Arts, Science and Technology, University of Northampton. Dr Ofer Engel is a Data Scientist at the University of Groningen.
A Hands-on Introduction to Big Data Analytics
by Funmi Obembe Ofer EngelThis practical textbook offers a hands-on introduction to big data analytics, helping you to develop the skills required to hit the ground running as a data professional. It complements theoretical foundations with an emphasis on the application of big data analytics, illustrated by real-life examples and datasets. Containing comprehensive coverage of all the key topics in this area, this book uses open-source technologies and examples in Python and Apache Spark. Learning features include: - Ethics by Design encourages you to consider data ethics at every stage. - Industry Insights facilitate a deeper understanding of the link between what you are studying and how it is applied in industry. - Datasets, questions, and exercises give you the opportunity to apply your learning. Dr Funmi Obembe is the Head of Technology at the Faculty of Arts, Science and Technology, University of Northampton. Dr Ofer Engel is a Data Scientist at the University of Groningen.
Hands-On Machine Learning with R (Chapman & Hall/CRC The R Series)
by Brad Boehmke Brandon M. GreenwellHands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today&’s most popular machine learning methods. This book serves as a practitioner&’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R&’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.
Hands-On Math Projects With Real-Life Applications: Grades 6-12 (J-B Ed: Hands On #27)
by Judith A Muschla Gary Robert MuschlaThe second edition of this hands-on math guide features sixty engaging projects for students in grades six to twelve learn math concepts and skills. This book is filled with classroom-tested projects that help students build skills in problem solving, critical thinking, and decision making. They also support a positive group environment by emphasize cooperative learning, group sharing, verbalizing ideas, and research skills, as well as writing clearly in mathematics and across other subject areas. Each of the projects follows the same proven format and includes instructions for the teacher, a Student Guide, and one or more reproducible datasheets and worksheets. They all include the elements needed for a successful individual or group learning experience. This second edition includes new projects and information about technology-based and e-learning strategies.Hands-On Math Projects with Real-Life Applications includes a special Skills Index that identifies the skills emphasized in each project. This book will save you time and help you instill in your students a genuine appreciation for the world of mathematics.
Hands-On Mathematics for Deep Learning: Build A Solid Mathematical Foundation For Training Efficient Deep Neural Networks
by Jay DawaniThis book is for data scientists, machine learning developers, aspiring deep learning developers or anyone who wants to understand the foundation of deep learning by learning the math behind it. Working knowledge of the Python programming language and machine learning basics is required.
Hands-On Mobile Development with .NET Core: Build cross-platform mobile applications with Xamarin, Visual Studio 2019, and .NET Core 3
by Can BilginDevelop native applications for multiple mobile and desktop platforms including but not limited to iOS, Android, and UWP with the Xamarin framework and Xamarin.FormsKey FeaturesUnderstand .NET Core and its cross-platform development philosophy Build Android, iOS, and Windows mobile applications with C#, .NET Core, and Azure Cloud ServicesBring Artificial Intelligence capabilities into your mobile applications with Azure AIBook Description.NET Core is the general umbrella term used for Microsoft’s cross-platform toolset. Xamarin used for developing mobile applications, is one of the app model implementations for .NET Core infrastructure. In this book, you will learn how to design, architect, and develop highly attractive, maintainable, efficient, and robust mobile applications for multiple platforms, including iOS, Android, and UWP, with the toolset provided by Microsoft using Xamarin, .NET Core, and Azure Cloud Services. This book will take you through various phases of application development with Xamarin, from environment setup, design, and architecture to publishing, using real-world scenarios. Throughout the book, you will learn how to develop mobile apps using Xamarin, Xamarin.Forms and .NET Standard; implement a webbased backend composed of microservices with .NET Core using various Azure services including but not limited to Azure App Services, Azure Active Directory, Notification Hub, Logic Apps, and Azure Functions, Cognitive Services; create data stores using popular database technologies such as Cosmos DB, SQL and Realm.Towards the end, the book will help developers to set up an efficient and maintainable development pipeline to manage the application life cycle using Visual Studio App Center and Visual Studio Services.What you will learnImplement native applications for multiple mobile and desktop platformsUnderstand and use various Azure Services with .NET CoreMake use of architectural patterns designed for mobile and web applicationsUnderstand the basic Cosmos DB conceptsUnderstand how different app models can be used to create an app serviceExplore the Xamarin and Xamarin.Forms UI suite with .NET Core for building mobile applicationsWho this book is forThis book is for mobile developers who wish to develop cross-platform mobile applications. Programming experience with C# is required. Some knowledge and understanding of core elements and cross-platform application development with .NET is required.
Hands-On Prescriptive Analytics: Optimizing Your Decision Making with Python
by Walter R. PaczkowskiBusiness decisions in any context—operational, tactical, or strategic—can have considerable consequences. Whether the outcome is positive and rewarding or negative and damaging to the business, its employees, and stakeholders is unknown when action is approved. These decisions are usually made under the proverbial cloud of uncertainty.With this practical guide, data analysts, data scientists, and business analysts will learn why and how maximizing positive consequences and minimizing negative ones requires three forms of rich information: Descriptive analytics explores the results from an action—what has already happened. Predictive analytics focuses on what could happen. The third, prescriptive analytics, informs us what should happen in the future.While all three are important for decision-makers, the primary focus of this book is on the third: prescriptive analytics. Author Walter R. Paczkowski, Ph.D. shows you:The distinction among descriptive, predictive, and prescriptive analyticsHow predictive analytics produces a menu of action optionsHow prescriptive analytics narrows the menu of action optionsThe forms of prescriptive analytics: eight prescriptive methodsTwo broad classes of these methods: non-stochastic and stochasticHow to develop prescriptive analyses for action recommendationsWays to use an appropriate tool-set in Python
Hands-On Programming with R: Write Your Own Functions and Simulations
by Garrett GrolemundLearn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you’ll learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions, and use all of R’s programming tools.RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You’ll gain valuable programming skills and support your work as a data scientist at the same time.Work hands-on with three practical data analysis projects based on casino gamesStore, retrieve, and change data values in your computer’s memoryWrite programs and simulations that outperform those written by typical R usersUse R programming tools such as if else statements, for loops, and S3 classesLearn how to write lightning-fast vectorized R codeTake advantage of R’s package system and debugging toolsPractice and apply R programming concepts as you learn them
Hands-On Qt for Python Developers: Build cross-platform GUI applications with Python and Qt 5
by Volodymyr KirichinetsBoost UI development with ready-made widgets, controls, charts, and data visualization and create stunning 2D and 3D graphics with PyQt and PySide2.Key FeaturesBuild optimized GUI applications by implementing multiprocessing and concurrencyUnderstand embedded and mobile development with PyQt and PySideLearn to create magnificent GUI applications using Pyside2 and QtQuick/QMLBook DescriptionQt is one of the most widely used and flexible frameworks for GUI application development, allowing you to write your application once and then deploy it to multiple operating systems. This book combines the best of Python and Qt to help you develop GUI applications with Python bindings, such as PyQt and PySide, that will supercharge your Python applications.The book begins with an overview of Qt and QML. You’ll start by working with PyQt GUI elements to style your applications. Then, you will learn how to use QWidget, frames, labels, and text fields, and work with graphics. This will be followed by taking you through how elements in the application communicate with each other by understanding signals, slots, and event handlers. This book will help you to gain a better understanding of the Qt framework and the tools to resolve issues when testing, linking, debugging, and multithreading your Python GUI applications. Finally, the book will help you get to grips with embedded and mobile development using PyQt and PySide.By the end of the book, you will be able to create modern, responsive, cross-platform desktop applications with the power of Qt, Python, and QML.What you will learnExplore PyQt5 and PySide2 to create comprehensive GUI applicationsFind out how threading and multiprocessing workUnderstand how to style GUIs with PyQtGet to grips with implementing buttonsUnderstand how elements communicate with signals, slots, and event handlersExplore mobile development with PyQt and PySideWho this book is forThis book is for Python developers who want to develop GUIs and cross-platform applications that are modern, responsive, and attractive. No prior knowledge of Qt or QML is required.
Hands-On Reactive Programming with Clojure: Create asynchronous, event-based, and concurrent applications, 2nd Edition
by Leonardo Borges Konrad SzydloLearn how to use RxClojure to deal with stateful computations Key Features Leverage the features of Functional Reactive Programming using Clojure Create dataflow-based systems that are the building blocks of Reactive Programming Use different Functional Reactive Programming frameworks, techniques, and patterns to solve real-world problems Book Description Reactive Programming is central to many concurrent systems, and can help make the process of developing highly concurrent, event-driven, and asynchronous applications simpler and less error-prone. This book will allow you to explore Reactive Programming in Clojure 1.9 and help you get to grips with some of its new features such as transducers, reader conditionals, additional string functions, direct linking, and socket servers. Hands-On Reactive Programming with Clojure starts by introducing you to Functional Reactive Programming (FRP) and its formulations, as well as showing you how it inspired Compositional Event Systems (CES). It then guides you in understanding Reactive Programming as well as learning how to develop your ability to work with time-varying values thanks to examples of reactive applications implemented in different frameworks. You'll also gain insight into some interesting Reactive design patterns such as the simple component, circuit breaker, request-response, and multiple-master replication. Finally, the book introduces microservices-based architecture in Clojure and closes with examples of unit testing frameworks. By the end of the book, you will have gained all the knowledge you need to create applications using different Reactive Programming approaches. What you will learn Understand how to think in terms of time-varying values and event streams Create, compose, and transform observable sequences using Reactive extensions Build a CES framework from scratch using core.async as its foundation Develop a simple ClojureScript game using Reagi Integrate Om and RxJS in a web application Implement a reactive API in Amazon Web Services (AWS) Discover helpful approaches to backpressure and error handling Get to grips with futures and their applications Who this book is for If you're interested in using Reactive Programming to build asynchronous and concurrent applications, this is the book for you. Basic knowledge of Clojure programming is necessary to understand the concepts covered in this book.
Hands-On RESTful Web Services with TypeScript 3: Design and develop scalable RESTful APIs for your applications
by Biharck AraújoThe book is aimed at web developers who have a basic understanding of the REST concepts and want to familiarize themselves with the idea of designing and developing RESTful APIs.
Hands-On Science and Math: Fun, Fascinating Activities for Young Children
by Beth R. DavisEncourage young investigators to feel, listen, smell, taste, and see their way to discovery by seamlessly infusing math and science throughout the school day! As you incorporate all five senses into learning experiences, you will give little innovators the opportunity to observe and explore the world around them. The activities in Hands-On Science and Math: Fun, Fascinating Activities for Young Children will help you plan engaging science, technology, engineering, and math (STEM) lessons that will excite children and foster their critical thinking. Children can experience the thrill of scientific inquiry through simple experiments. Designed to work with easy-to-find materials, the Hands-On Science and Math activities are inexpensive and uncomplicated, yet they lay the groundwork for understanding more complex STEM concepts later on.
Hands-On Simulation Modeling with Python: Develop simulation models for improved efficiency and precision in the decision-making process, 2nd Edition
by Giuseppe CiaburroLearn to construct state-of-the-art simulation models with Python and enhance your simulation modelling skills, as well as create and analyze digital prototypes of physical models with easeKey FeaturesUnderstand various statistical and physical simulations to improve systems using PythonLearn to create the numerical prototype of a real model using hands-on examplesEvaluate performance and output results based on how the prototype would work in the real worldBook DescriptionSimulation modelling is an exploration method that aims to imitate physical systems in a virtual environment and retrieve useful statistical inferences from it. The ability to analyze the model as it runs sets simulation modelling apart from other methods used in conventional analyses. This book is your comprehensive and hands-on guide to understanding various computational statistical simulations using Python. The book begins by helping you get familiarized with the fundamental concepts of simulation modelling, that'll enable you to understand the various methods and techniques needed to explore complex topics. Data scientists working with simulation models will be able to put their knowledge to work with this practical guide. As you advance, you'll dive deep into numerical simulation algorithms, including an overview of relevant applications, with the help of real-world use cases and practical examples. You'll also find out how to use Python to develop simulation models and how to use several Python packages. Finally, you'll get to grips with various numerical simulation algorithms and concepts, such as Markov Decision Processes, Monte Carlo methods, and bootstrapping techniques.By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.What you will learnGet to grips with the concept of randomness and the data generation processDelve into resampling methodsDiscover how to work with Monte Carlo simulationsUtilize simulations to improve or optimize systemsFind out how to run efficient simulations to analyze real-world systemsUnderstand how to simulate random walks using Markov chainsWho this book is forThis book is for data scientists, simulation engineers, and anyone who is already familiar with the basic computational methods and wants to implement various simulation techniques such as Monte-Carlo methods and statistical simulation using Python.