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Hands-On Automated Machine Learning
Automate data and model pipelines for faster machine learning applicationsAbout This Book• Build automated modules for different machine learning components• Understand each component of a machine learning pipeline in depth• Learn to use different open source AutoML and feature engineering platformsWho This Book Is ForIf you're a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book is ideal for you.You'll also find this book useful if you're an ML engineer or data professional interested in developing quick machine learning pipelines for your projects.Prior exposure to Python programming will help you get the best out of this book. What You Will Learn• Understand the fundamentals of Automated Machine Learning systems• Explore auto-sklearn and MLBox for AutoML tasks • Automate your preprocessing methods along with feature transformation• Enhance feature selection and generation using the Python stack• Assemble individual components of ML into a complete AutoML framework• Demystify hyperparameter tuning to optimize your ML models• Dive into Machine Learning concepts such as neural networks and autoencoders • Understand the information costs and trade-offs associated with AutoMLIn DetailAutoML is designed to automate parts of Machine Learning.Readily available AutoML tools are making data science practitioners' work easy and are received well in the advanced analytics community.Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible.In this book, you'll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more.In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning.By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you'll be able to incorporate automation tasks using practical datasets.You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions. Style and approachStep by step approach to understand how to automate your machine learning tasks
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Hands-on Rust : Effective Learning through 2D Game Development and Play
Rust is an exciting new programming language combining the power of C with memory safety, fearless concurrency, and productivity boosters - and what better way to learn than by making games.Each chapter in this book presents hands-on, practical projects ranging from "Hello, World" to building a full dungeon crawler game.With this book, you'll learn game development skills applicable to other engines, including Unity and Unreal. Rust is an exciting programming language combining the power of C with memory safety, fearless concurrency, and productivity boosters.With Rust, you have a shiny new playground where your game ideas can flourish. Each chapter in this book presents hands-on, practical projects that take you on a journey from "Hello, World" to building a full dungeon crawler game.Start by setting up Rust and getting comfortable with your development environment.Learn the language basics with practical examples as you make your own version of Flappy Bird.Discover what it takes to randomly generate dungeons and populate them with monsters as you build a complete dungeon crawl game.Run game systems concurrently for high-performance and fast game-play, while retaining the ability to debug your program.Unleash your creativity with magical items, tougher monsters, and intricate dungeon design.Add layered graphics and polish your game with style. What You Need:A computer running Windows 10, Linux, or Mac OS X. A text editor, such as Visual Studio Code. A video card and drivers capable of running OpenGL 3.2.
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Hands-On Machine Learning with R
Hands-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.
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Programming Massively Parallel Processors : A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture.Various techniques for constructing parallel programs are explored in detail.Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs.Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. For this new edition, the authors are updating their coverage of CUDA, including the concept of unified memory, and expanding content in areas such as threads, while still retaining its concise, intuitive, practical approach based on years of road-testing in the authors' own parallel computing courses.
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Is learning programming and software development very challenging?
Learning programming and software development can be challenging for some people, as it requires logical thinking, problem-solving skills, and attention to detail. However, with dedication, practice, and the right resources, it is definitely achievable. Breaking down complex concepts into smaller, more manageable parts and seeking help from online tutorials, courses, and communities can make the learning process easier and more enjoyable. Ultimately, the level of challenge will vary depending on the individual's background, experience, and learning style.
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Was lye poured on hands?
Yes, historically, lye was used as a caustic substance to clean and disinfect hands. It was commonly used in soap-making processes to break down fats and oils. However, due to its harsh nature and potential skin irritation, lye is not recommended for direct use on hands in modern times.
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How does callus form on the hands through strength training?
Calluses form on the hands through strength training as a natural response to repeated friction and pressure on the skin. When performing exercises like weightlifting or using equipment like pull-up bars, the skin on the hands can become irritated and develop calluses as a protective mechanism. Over time, the skin thickens and hardens in areas that are subjected to frequent stress, resulting in the formation of calluses. While calluses can help prevent blisters and provide some protection, it is important to properly care for them to avoid any discomfort or complications.
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Which programming languages are used in software development?
There are many programming languages used in software development, including popular languages such as Java, Python, C++, JavaScript, and Ruby. Each language has its own strengths and is used for different purposes in software development. For example, Java is commonly used for building enterprise-level applications, while Python is known for its simplicity and versatility. C++ is often used for system software and game development, while JavaScript is essential for web development. Overall, the choice of programming language depends on the specific requirements of the software being developed.
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Hands-On Object-Oriented Programming with C# : Build maintainable software with reusable code using C#
Enhance your programming skills by learning the intricacies of object oriented programming in C# 8Key FeaturesUnderstand the four pillars of OOP; encapsulation, inheritance, abstraction and polymorphismLeverage the latest features of C# 8 including nullable reference types and Async StreamsExplore various design patterns, principles, and best practices in OOPBook DescriptionObject-oriented programming (OOP) is a programming paradigm organized around objects rather than actions, and data rather than logic.With the latest release of C#, you can look forward to new additions that improve object-oriented programming.This book will get you up to speed with OOP in C# in an engaging and interactive way.The book starts off by introducing you to C# language essentials and explaining OOP concepts through simple programs.You will then go on to learn how to use classes, interfacesm and properties to write pure OOP code in your applications.You will broaden your understanding of OOP further as you delve into some of the advanced features of the language, such as using events, delegates, and generics.Next, you will learn the secrets of writing good code by following design patterns and design principles.You'll also understand problem statements with their solutions and learn how to work with databases with the help of ADO.NET.Further on, you'll discover a chapter dedicated to the Git version control system.As you approach the conclusion, you'll be able to work through OOP-specific interview questions and understand how to tackle them.By the end of this book, you will have a good understanding of OOP with C# and be able to take your skills to the next level. What you will learnMaster OOP paradigm fundamentals Explore various types of exceptions Utilize C# language constructs efficiently Solve complex design problems by understanding OOP Understand how to work with databases using ADO.NET Understand the power of generics in C#Get insights into the popular version control system, Git Learn how to model and design your softwareWho this book is forThis book is designed for people who are new to object-oriented programming.Basic C# skills are assumed, however, prior knowledge of OOP in any other language is not required.
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A Hands-On Introduction to Machine Learning
Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply.It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science.All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry.While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility.A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides.Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book.
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Hardware Security : A Hands-on Learning Approach
Hardware Security: A Hands-On Learning Approach provides a broad, comprehensive and practical overview of hardware security that encompasses all levels of the electronic hardware infrastructure.It covers basic concepts like advanced attack techniques and countermeasures that are illustrated through theory, case studies and well-designed, hands-on laboratory exercises for each key concept.The book is ideal as a textbook for upper-level undergraduate students studying computer engineering, computer science, electrical engineering, and biomedical engineering, but is also a handy reference for graduate students, researchers and industry professionals.For academic courses, the book contains a robust suite of teaching ancillaries. Users will be able to access schematic, layout and design files for a printed circuit board for hardware hacking (i.e. the HaHa board) that can be used by instructors to fabricate boards, a suite of videos that demonstrate different hardware vulnerabilities, hardware attacks and countermeasures, and a detailed description and user manual for companion materials.
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Hands-on Intermediate Econometrics Using R: Templates For Learning Quantitative Methods And R Software
How to learn both applied statistics (econometrics) and free, open-source software R?This book allows students to have a sense of accomplishment by copying and pasting many hands-on templates provided here.The textbook is essential for anyone wishing to have a practical understanding of an extensive range of topics in Econometrics.No other text provides software snippets to learn so many new statistical tools with hands-on examples.The explicit knowledge of inputs and outputs of each new method allows the student to know which algorithm is worth studying.The book offers sufficient theoretical and algorithmic details about a vast range of statistical techniques.The second edition's preface lists the following topics generally absent in other textbooks. (i) Iteratively reweighted least squares, (ii) Pillar charts to represent 3D data. (iii) Stochastic frontier analysis (SFA) (iv) model selection with Mallows' Cp criterion. (v) Hodrick-Prescott (HP) filter. (vi) Automatic ARIMA models. (vi) Nonlinear Granger-causality using kernel regressions and bootstrap confidence intervals. (vii) new Keynesian Phillips curve (NKPC). (viii) Market-neutral pairs trading using two cointegrated stocks. (ix) Artificial neural network (ANN) for product-specific forecasting. (x) Vector AR and VARMA models. (xi) New tools for diagnosing the endogeneity problem. (xii) The elegant set-up of k-class estimators and identification. (xiii) Probit-logit models and Heckman selection bias correction. (xiv) Receiver operating characteristic (ROC) curves and areas under them. (xv) Confusion matrix. (xvi) Quantile regression (xvii) Elastic net estimator. (xviii) generalized Correlations (xix) maximum entropy bootstrap for time series. (xx) Convergence concepts quantified. (xxi) Generalized partial correlation coefficients (xxii) Panel data and duration (survival) models.
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Should one still focus on learning traditional programming languages or specialize in web development?
It ultimately depends on an individual's career goals and interests. Traditional programming languages such as Java, C++, and Python are still widely used in various industries and can provide a strong foundation in computer science principles. On the other hand, specializing in web development can be a lucrative career path, as the demand for web developers continues to grow. It may be beneficial to have a strong understanding of traditional programming languages while also gaining expertise in web development to have a well-rounded skill set.
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What is a hands-on history?
Hands-on history refers to a learning approach that actively engages students in historical experiences and activities. It involves using tangible objects, reenactments, and interactive projects to help students better understand and connect with historical events and time periods. This approach allows students to immerse themselves in the past, fostering a deeper understanding and appreciation for history. Hands-on history can include activities such as visiting historical sites, handling artifacts, and participating in historical simulations.
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Do hair grow on your hands?
Yes, hair does grow on the hands. Hair follicles are present all over the body, including the hands, and can produce fine, light-colored hair. However, the hair on the hands is usually much finer and less noticeable compared to the hair on other parts of the body. Factors such as genetics, hormones, and age can influence the amount and thickness of hair growth on the hands.
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What is this on my hands?
It is difficult to determine what is on your hands without more information. It could be dirt, paint, lotion, or any number of substances. If you are concerned about the substance on your hands, it may be best to wash them with soap and water to remove it. If the substance does not come off easily or if you are experiencing any discomfort, it may be best to seek medical advice.
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