Data Science Revealed
Get insight into data science techniques such as data engineering and visualization, statistical modeling, machine learning, and deep learning. This book teaches you how to select variables, optimize hyper parameters, develop pipelines, and train, test, and validate machine and deep learning models. Each chapter includes a set of examples allowing you to understand the concepts, assumptions, and procedures behind each model. The book covers parametric methods or linear models that combat under- or over-fitting using techniques such as Lasso and Ridge. It includes complex regression analysis with time series smoothing, decomposition, and forecasting. It takes a fresh look at non-parametric models for binary classification (logistic regression analysis) and ensemble methods such as decision trees, support vector machines, and naive Bayes. It covers the most popular non-parametric method for time-event data (the Kaplan-Meier estimator). It also covers ways of solving classification pro ...
Get insight into data science techniques such as data engineering and visualization, statistical modeling, machine learning, and deep learning. This book teaches you how to select variables, optimize hyper parameters, develop pipelines, and train, test, and validate machine and deep learning models. Each chapter includes a set of examples allowing you to understand the concepts, assumptions, and procedures behind each model. The book covers parametric methods or linear models that combat under- or over-fitting using techniques such as Lasso and Ridge. It includes complex regression analysis with time series smoothing, decomposition, and forecasting. It takes a fresh look at non-parametric models for binary classification (logistic regression analysis) and ensemble methods such as decision trees, support vector machines, and naive Bayes. It covers the most popular non-parametric method for time-event data (the Kaplan-Meier estimator). It also covers ways of solving classification pro ...
Data Structures and Algorithms
Data Structures and Algorithms (DSA) features implementations of data structures and algorithms that are not implemented in any version of .NET. This book is the result of a series of emails sent back and forth between the two authors during the development of a library for the .NET framework of the same name. A key factor of this book and its associated implementations is that all algorithms were designed by us, using the theory of the algorithm in question as a guideline. The book use's pseudo code to describe the solutions that we have created so that it can be easily ported to many imperative OO languages like C#, C++, and Java (amongst others). ...
Data Structures and Algorithms (DSA) features implementations of data structures and algorithms that are not implemented in any version of .NET. This book is the result of a series of emails sent back and forth between the two authors during the development of a library for the .NET framework of the same name. A key factor of this book and its associated implementations is that all algorithms were designed by us, using the theory of the algorithm in question as a guideline. The book use's pseudo code to describe the solutions that we have created so that it can be easily ported to many imperative OO languages like C#, C++, and Java (amongst others). ...
Robust Python
Does it seem like your Python projects are getting bigger and bigger? Are you feeling the pain as your codebase expands and gets tougher to debug and maintain? Python is an easy language to learn and use, but that also means systems can quickly grow beyond comprehension. Thankfully, Python has features to help developers overcome maintainability woes. In this practical book, author Patrick Viafore shows you how to use Python's type system to the max. You'll look at user-defined types, such as classes and enums, and Python's type hinting system. You'll also learn how to make Python extensible and how to use a comprehensive testing strategy as a safety net. With these tips and techniques, you'll write clearer and more maintainable code. Learn why types are essential in modern development ecosystems; Understand how type choices such as classes, dictionaries, and enums reflect specific intents; Make Python extensible for the future without adding bloat; Use popular Python tools to in ...
Does it seem like your Python projects are getting bigger and bigger? Are you feeling the pain as your codebase expands and gets tougher to debug and maintain? Python is an easy language to learn and use, but that also means systems can quickly grow beyond comprehension. Thankfully, Python has features to help developers overcome maintainability woes. In this practical book, author Patrick Viafore shows you how to use Python's type system to the max. You'll look at user-defined types, such as classes and enums, and Python's type hinting system. You'll also learn how to make Python extensible and how to use a comprehensive testing strategy as a safety net. With these tips and techniques, you'll write clearer and more maintainable code. Learn why types are essential in modern development ecosystems; Understand how type choices such as classes, dictionaries, and enums reflect specific intents; Make Python extensible for the future without adding bloat; Use popular Python tools to in ...
Cloud Without Compromise
Many companies claim to have "gone to the cloud," yet returns from their efforts are meager or worse. Why? Because they've defined cloud as a destination, not a capability. Using cloud as a single-vendor, one-stop destination is fiction; in practice, today's organizations use a mosaic of capabilities across several vendors. Your cloud strategy needs to follow a hybrid multicloud model, one that delivers cloud's value at destinations you choose. This practical guide provides business leaders and C-level executives with guidance and insights across a wide range of cloud-related topics, such as distributed cloud, microservices, and other open source solutions for strengthening operations. You'll apply in-the-field best practices and lessons learned as you define your hybrid cloud strategy and drive your company's transformation strategy. Learn cloud fundamentals and patterns, including basic concepts and history; Get a framework for cloud acumen phases to value-plot your cloud futur ...
Many companies claim to have "gone to the cloud," yet returns from their efforts are meager or worse. Why? Because they've defined cloud as a destination, not a capability. Using cloud as a single-vendor, one-stop destination is fiction; in practice, today's organizations use a mosaic of capabilities across several vendors. Your cloud strategy needs to follow a hybrid multicloud model, one that delivers cloud's value at destinations you choose. This practical guide provides business leaders and C-level executives with guidance and insights across a wide range of cloud-related topics, such as distributed cloud, microservices, and other open source solutions for strengthening operations. You'll apply in-the-field best practices and lessons learned as you define your hybrid cloud strategy and drive your company's transformation strategy. Learn cloud fundamentals and patterns, including basic concepts and history; Get a framework for cloud acumen phases to value-plot your cloud futur ...
TensorFlow 2 Pocket Reference
This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself. When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the training process? How do you leverage a pretrained model using transfer learning? How do you perform hyperparameter tuning? Pick up this pocket reference and reduce the time you spend searching through options for your TensorFlow use cases. Understand best practices in TensorFlow model patterns and ML workflows; Use code snippets as templates in building TensorFlow models and workflows; Save development time by integrating prebuilt models in TensorFlow Hub; Make informed design choices about data ingestion, training paradigms, model saving, and inferencing; Address common scenari ...
This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself. When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the training process? How do you leverage a pretrained model using transfer learning? How do you perform hyperparameter tuning? Pick up this pocket reference and reduce the time you spend searching through options for your TensorFlow use cases. Understand best practices in TensorFlow model patterns and ML workflows; Use code snippets as templates in building TensorFlow models and workflows; Save development time by integrating prebuilt models in TensorFlow Hub; Make informed design choices about data ingestion, training paradigms, model saving, and inferencing; Address common scenari ...
PowerShell Cookbook, 4th Edition
How do you use PowerShell to navigate the filesystem, manage files and folders, or retrieve a web page? This introduction to the PowerShell language and scripting environment provides more than 400 task-oriented recipes to help you solve all kinds of problems. Intermediate to advanced system administrators will find more than 100 tried-and-tested scripts they can copy and use immediately. Updated for PowerShell 5.1 and Open Source PowerShell up to 7.0 and beyond, this comprehensive cookbook includes hands-on recipes for common tasks and administrative jobs that you can apply whether you're on the client or server version of Windows. You also get quick references to technologies used in conjunction with PowerShell, including regular expressions, the XPath language, format specifiers, and frequently referenced .NET, COM, and WMI classes. Learn how to use PowerShell on Windows 10 and Windows Server 2019; Tour PowerShell's core features, including the command model, object-based pipe ...
How do you use PowerShell to navigate the filesystem, manage files and folders, or retrieve a web page? This introduction to the PowerShell language and scripting environment provides more than 400 task-oriented recipes to help you solve all kinds of problems. Intermediate to advanced system administrators will find more than 100 tried-and-tested scripts they can copy and use immediately. Updated for PowerShell 5.1 and Open Source PowerShell up to 7.0 and beyond, this comprehensive cookbook includes hands-on recipes for common tasks and administrative jobs that you can apply whether you're on the client or server version of Windows. You also get quick references to technologies used in conjunction with PowerShell, including regular expressions, the XPath language, format specifiers, and frequently referenced .NET, COM, and WMI classes. Learn how to use PowerShell on Windows 10 and Windows Server 2019; Tour PowerShell's core features, including the command model, object-based pipe ...
Azure DevOps Succinctly
The complexity of software development requires coordination and collaboration between all teams involved to guarantee that the client - whether a customer or another team in-house - is satisfied. DevOps is one strategy for achieving successful development, testing, and deployment, and Microsoft Azure provides a collection of tools and services that help facilitate a productive DevOps environment. In Azure DevOps Succinctly, author Sander Rossel covers the basics to get you up and running with Boards, Repos, Pipelines, Test Plans, and more. Download the book today to learn how you can quickly enhance your team's DevOps processes by integrating with Azure. ...
The complexity of software development requires coordination and collaboration between all teams involved to guarantee that the client - whether a customer or another team in-house - is satisfied. DevOps is one strategy for achieving successful development, testing, and deployment, and Microsoft Azure provides a collection of tools and services that help facilitate a productive DevOps environment. In Azure DevOps Succinctly, author Sander Rossel covers the basics to get you up and running with Boards, Repos, Pipelines, Test Plans, and more. Download the book today to learn how you can quickly enhance your team's DevOps processes by integrating with Azure. ...
The Official Raspberry Pi Handbook 2021
To help you get the most of out of your Raspberry Pi computer, this official Handbook features 200 pages of essential information, inspiring projects, practical tutorials, and definitive reviews. Learn how to set up your Raspberry Pi and start using it; Discover the new Raspberry Pi 400 and High Quality Camera; Be inspired by incredible projects made by other people; Learn how to code and make with our step-by-step tutorials; Find out about the top kits and accessories for your projects. ...
To help you get the most of out of your Raspberry Pi computer, this official Handbook features 200 pages of essential information, inspiring projects, practical tutorials, and definitive reviews. Learn how to set up your Raspberry Pi and start using it; Discover the new Raspberry Pi 400 and High Quality Camera; Be inspired by incredible projects made by other people; Learn how to code and make with our step-by-step tutorials; Find out about the top kits and accessories for your projects. ...
Learn Quantum Computing with Python and Q#
Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you'll build your own quantum simulator and apply quantum programming techniques to real-world examples including cryptography and chemical analysis. Quantum computers present a radical leap in speed and computing power. Improved scientific simulations and new frontiers in cryptography that are impossible with classical computing may soon be in reach. Microsoft's Quantum Development Kit and the Q# language give you the tools to experiment with quantum computing without knowing advanced math or theoretical physics. Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Use Python to build your own quantum simulator and take advantage of Microsoft's open source tools to fine-tune quantum algorithms. The authors explain complex math and theory through stories, visuals, and games. You'll learn to apply quant ...
Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you'll build your own quantum simulator and apply quantum programming techniques to real-world examples including cryptography and chemical analysis. Quantum computers present a radical leap in speed and computing power. Improved scientific simulations and new frontiers in cryptography that are impossible with classical computing may soon be in reach. Microsoft's Quantum Development Kit and the Q# language give you the tools to experiment with quantum computing without knowing advanced math or theoretical physics. Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Use Python to build your own quantum simulator and take advantage of Microsoft's open source tools to fine-tune quantum algorithms. The authors explain complex math and theory through stories, visuals, and games. You'll learn to apply quant ...
Financial Numerical Recipes in C++
This book is a a discussion of the calculation of specific formulas in finance. The field of finance has seen a rapid development in recent years, with increasing mathematical sophistication. While the formalization of the field can be traced back to the work of Markowitz (1952) on investors mean-variance decisions and Modigliani and Miller (1958) on the capital structure problem, it was the solution for the price of a call option by Black and Scholes (1973); Merton (1973) which really was the starting point for the mathematicalization of finance. The fields of derivatives and fixed income have since then been the main fields where complicated formulas are used. This book is intended to be of use for people who want to both understand and use these formulas, which explains why most of the algorithms presented later are derivatives prices. This project started when I was teaching a course in derivatives at the University of British Columbia, in the course of which I sat down and wrot ...
This book is a a discussion of the calculation of specific formulas in finance. The field of finance has seen a rapid development in recent years, with increasing mathematical sophistication. While the formalization of the field can be traced back to the work of Markowitz (1952) on investors mean-variance decisions and Modigliani and Miller (1958) on the capital structure problem, it was the solution for the price of a call option by Black and Scholes (1973); Merton (1973) which really was the starting point for the mathematicalization of finance. The fields of derivatives and fixed income have since then been the main fields where complicated formulas are used. This book is intended to be of use for people who want to both understand and use these formulas, which explains why most of the algorithms presented later are derivatives prices. This project started when I was teaching a course in derivatives at the University of British Columbia, in the course of which I sat down and wrot ...