Mastering Python for Bioinformatics
Life scientists today urgently need training in bioinformatics skills. Too many bioinformatics programs are poorly written and barely maintained, usually by students and researchers who've never learned basic programming skills. This practical guide shows postdoc bioinformatics professionals and students how to exploit the best parts of Python to solve problems in biology while creating documented, tested, reproducible software. Ken Youens-Clark, author of Tiny Python Projects (Manning), demonstrates not only how to write effective Python code but also how to use tests to write and refactor scientific programs. You'll learn the latest Python features and tools including linters, formatters, type checkers, and tests to create documented and tested programs. You'll also tackle 14 challenges in Rosalind, a problem-solving platform for learning bioinformatics and programming. - Create command-line Python programs to document and validate parameters - Write tests to verify refactor p ...
Life scientists today urgently need training in bioinformatics skills. Too many bioinformatics programs are poorly written and barely maintained, usually by students and researchers who've never learned basic programming skills. This practical guide shows postdoc bioinformatics professionals and students how to exploit the best parts of Python to solve problems in biology while creating documented, tested, reproducible software. Ken Youens-Clark, author of Tiny Python Projects (Manning), demonstrates not only how to write effective Python code but also how to use tests to write and refactor scientific programs. You'll learn the latest Python features and tools including linters, formatters, type checkers, and tests to create documented and tested programs. You'll also tackle 14 challenges in Rosalind, a problem-solving platform for learning bioinformatics and programming. - Create command-line Python programs to document and validate parameters - Write tests to verify refactor p ...
Introducing .NET for Apache Spark
Get started using Apache Spark via C# or F# and the .NET for Apache Spark bindings. This book is an introduction to both Apache Spark and the .NET bindings. Readers new to Apache Spark will get up to speed quickly using Spark for data processing tasks performed against large and very large datasets. You will learn how to combine your knowledge of .NET with Apache Spark to bring massive computing power to bear by distributed processing of extremely large datasets across multiple servers. This book covers how to get a local instance of Apache Spark running on your developer machine and shows you how to create your first .NET program that uses the Microsoft .NET bindings for Apache Spark. Techniques shown in the book allow you to use Apache Spark to distribute your data processing tasks over multiple compute nodes. You will learn to process data using both batch mode and streaming mode so you can make the right choice depending on whether you are processing an existing dataset or are w ...
Get started using Apache Spark via C# or F# and the .NET for Apache Spark bindings. This book is an introduction to both Apache Spark and the .NET bindings. Readers new to Apache Spark will get up to speed quickly using Spark for data processing tasks performed against large and very large datasets. You will learn how to combine your knowledge of .NET with Apache Spark to bring massive computing power to bear by distributed processing of extremely large datasets across multiple servers. This book covers how to get a local instance of Apache Spark running on your developer machine and shows you how to create your first .NET program that uses the Microsoft .NET bindings for Apache Spark. Techniques shown in the book allow you to use Apache Spark to distribute your data processing tasks over multiple compute nodes. You will learn to process data using both batch mode and streaming mode so you can make the right choice depending on whether you are processing an existing dataset or are w ...
Practical Machine Learning for Computer Vision
This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability. Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras. You'll learn how to: Design ML architecture for computer vision tasks; Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropri ...
This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability. Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras. You'll learn how to: Design ML architecture for computer vision tasks; Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropri ...
Git for Programmers
Git is the most popular version control system in the world. It allows developers to keep up with frequent code changes in a project, ensures there are no code conflicts between the developers, and reverts to an older version of code when required. Git for Programmers comprehensively equips you with actionable insights on advanced Git concepts in an engaging and straightforward way. This book will help you gain expertise on Git with many practical use cases as you progress through the chapters. The book begins with a quick history of Git and instructions on how to get it and install it, after which you'll dive into the creation and cloning of your repository. As you progress through the book, you'll explore Git places, branching, and GUIs. Once you understand the fundamentals, you'll learn how to handle merge conflicts, rebase, amend, interactive rebase, and use the log. You'll also explore important Git commands for managing your repository. Finally, the book concludes with c ...
Git is the most popular version control system in the world. It allows developers to keep up with frequent code changes in a project, ensures there are no code conflicts between the developers, and reverts to an older version of code when required. Git for Programmers comprehensively equips you with actionable insights on advanced Git concepts in an engaging and straightforward way. This book will help you gain expertise on Git with many practical use cases as you progress through the chapters. The book begins with a quick history of Git and instructions on how to get it and install it, after which you'll dive into the creation and cloning of your repository. As you progress through the book, you'll explore Git places, branching, and GUIs. Once you understand the fundamentals, you'll learn how to handle merge conflicts, rebase, amend, interactive rebase, and use the log. You'll also explore important Git commands for managing your repository. Finally, the book concludes with c ...
OpenShift for Developers, 2nd Edition
Ready to build cloud native applications? Get a hands-on introduction to daily life as a developer crafting code on OpenShift, the open source container application platform from Red Hat. Creating and packaging your apps for deployment on modern distributed systems can be daunting. Too often, adding infrastructure value can complicate development. With this practical guide, you'll learn how to build, deploy, and manage a multitiered application on OpenShift. Authors Joshua Wood and Brian Tannous demonstrate how OpenShift speeds application development. With the Kubernetes container orchestrator at its core, OpenShift simplifies and automates the way you build, ship, and run code. You'll learn how to use OpenShift and the Quarkus Java framework to develop and deploy apps using proven enterprise technologies and practices that you can apply to code in any language. Learn the development cycles for building and deploying on OpenShift, and the tools that drive them; Use OpenShift to ...
Ready to build cloud native applications? Get a hands-on introduction to daily life as a developer crafting code on OpenShift, the open source container application platform from Red Hat. Creating and packaging your apps for deployment on modern distributed systems can be daunting. Too often, adding infrastructure value can complicate development. With this practical guide, you'll learn how to build, deploy, and manage a multitiered application on OpenShift. Authors Joshua Wood and Brian Tannous demonstrate how OpenShift speeds application development. With the Kubernetes container orchestrator at its core, OpenShift simplifies and automates the way you build, ship, and run code. You'll learn how to use OpenShift and the Quarkus Java framework to develop and deploy apps using proven enterprise technologies and practices that you can apply to code in any language. Learn the development cycles for building and deploying on OpenShift, and the tools that drive them; Use OpenShift to ...
Machine Learning for Financial Risk Management with Python
Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will: Review classical time series applications and compare them with deep learning models; Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning; Improve market risk models (VaR and ES) using ML techniques and including liquidity dimension; Develop a credit risk anal ...
Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will: Review classical time series applications and compare them with deep learning models; Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning; Improve market risk models (VaR and ES) using ML techniques and including liquidity dimension; Develop a credit risk anal ...
Tutorials of Visual Graphic Communication Programs for Interior Design
This open book is for the beginning level of both architecture and interior design students who learn computer graphic communication software. The author developed multiple tutorials to teach three computer graphic applications, AutoCAD, Revit, and Enscape. AutoCAD is an essential computer drafting software which is 2D drawing software. Revit is a Building Information Modeling software, which is 3D based modeling software. Lastly, Enscape is a real-time rendering, animation, and virtual reality plug-in for users' 4D experiences. ...
This open book is for the beginning level of both architecture and interior design students who learn computer graphic communication software. The author developed multiple tutorials to teach three computer graphic applications, AutoCAD, Revit, and Enscape. AutoCAD is an essential computer drafting software which is 2D drawing software. Revit is a Building Information Modeling software, which is 3D based modeling software. Lastly, Enscape is a real-time rendering, animation, and virtual reality plug-in for users' 4D experiences. ...
Computer Vision and Augmented Reality in iOS
Learn how computer vision works, how augmented reality renders digital graphics into the physical world via an iPhone's camera, and how to incorporate these technologies into your own apps. This book shows you how to take full advantage of computer vision technologies. Interacting with other people online usually involves user-generated images and videos; whether it be "memes", short videos, or heavily-modified images. Before smart phones, generating this content required a professional using high-level image and video editing software. Not any more. This book will teach you to use computer vision in the most popular ways, such as for facial recognition, image to text analysis and, of course, recording a video of a dancing hot dog in your living room. Starting with the history of computer vision, image and video processing fundamentals, and an introduction to developing augmented reality applications, you'll learn to incorporate computer vision both in the content you create and t ...
Learn how computer vision works, how augmented reality renders digital graphics into the physical world via an iPhone's camera, and how to incorporate these technologies into your own apps. This book shows you how to take full advantage of computer vision technologies. Interacting with other people online usually involves user-generated images and videos; whether it be "memes", short videos, or heavily-modified images. Before smart phones, generating this content required a professional using high-level image and video editing software. Not any more. This book will teach you to use computer vision in the most popular ways, such as for facial recognition, image to text analysis and, of course, recording a video of a dancing hot dog in your living room. Starting with the history of computer vision, image and video processing fundamentals, and an introduction to developing augmented reality applications, you'll learn to incorporate computer vision both in the content you create and t ...
Rust for Rustaceans
For developers who've mastered the basics, this book is the next step on your way to professional-level programming in Rust. It covers everything you need to build and maintain larger code bases, write powerful and flexible applications and libraries, and confidently expand the scope and complexity of your projects. Author Jon Gjengset takes you deep into the Rust programming language, dissecting core topics like ownership, traits, concurrency, and unsafe code. You'll explore key concepts like type layout and trait coherence, delve into the inner workings of concurrent programming and asynchrony with async/await, and take a tour of the world of no_std programming. Gjengset also provides expert guidance on API design, testing strategies, and error handling, and will help develop your understanding of foreign function interfaces, object safety, procedural macros, and much more. You'll Learn: How to design reliable, idiomatic, and ergonomic Rust programs based on best principles; Ef ...
For developers who've mastered the basics, this book is the next step on your way to professional-level programming in Rust. It covers everything you need to build and maintain larger code bases, write powerful and flexible applications and libraries, and confidently expand the scope and complexity of your projects. Author Jon Gjengset takes you deep into the Rust programming language, dissecting core topics like ownership, traits, concurrency, and unsafe code. You'll explore key concepts like type layout and trait coherence, delve into the inner workings of concurrent programming and asynchrony with async/await, and take a tour of the world of no_std programming. Gjengset also provides expert guidance on API design, testing strategies, and error handling, and will help develop your understanding of foreign function interfaces, object safety, procedural macros, and much more. You'll Learn: How to design reliable, idiomatic, and ergonomic Rust programs based on best principles; Ef ...
Machine Learning with PyTorch and Scikit-Learn
Machine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself. Why PyTorch? PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, th ...
Machine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself. Why PyTorch? PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, th ...