Quantum Machine Learning with Python
Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particles. It also examines Quantum machine learning, which can help solve some of the most challenging problems in forecasting, financial modeling, genomics, cybersecurity, supply chain logistics, cryptography among others. You'll start by reviewing the fundamental concepts of Quantum Computing, such as Dirac Notations, Qubits, and Bell state, followed by postulates and mathematical foundations of Quantum Computing. Once the foundation base is set, you'll delve deep into Quantum based algorithms including Quantum Fourier transform, phase estimation, and HHL (Harrow-Hassidim-Lloyd) among others. You'll then be introduced to Quantum machine learning and Quantum deep learning-based algorithms, ...
Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particles. It also examines Quantum machine learning, which can help solve some of the most challenging problems in forecasting, financial modeling, genomics, cybersecurity, supply chain logistics, cryptography among others. You'll start by reviewing the fundamental concepts of Quantum Computing, such as Dirac Notations, Qubits, and Bell state, followed by postulates and mathematical foundations of Quantum Computing. Once the foundation base is set, you'll delve deep into Quantum based algorithms including Quantum Fourier transform, phase estimation, and HHL (Harrow-Hassidim-Lloyd) among others. You'll then be introduced to Quantum machine learning and Quantum deep learning-based algorithms, ...
How To Manage Remote Servers with Ansible
This book is designed to introduce you to using Ansible to manage your servers. You'll learn how to install and configure Ansible on a control node, and then how to use it to configure and run commands on remote servers. You'll also learn how to collect tasks into complete Playbooks to automate server setup from start to finish. The topics that it covers include how to: - Become familiar with configuration management tools and processes, and the benefits of using them to manage your infrastructure. - Install and configure Ansible on an Ubuntu 20.04 control node, ensuring that your servers are properly set up and that you are able to execute remote instructions through Ansible. - Build inventory files and organize your servers into groups to selectively control how and where Ansible commands are run. - Run Ad Hoc commands to execute individual tasks on one, or multiple remote servers. - Package individual commands into Playbooks that you can use to automate the provisioning of m ...
This book is designed to introduce you to using Ansible to manage your servers. You'll learn how to install and configure Ansible on a control node, and then how to use it to configure and run commands on remote servers. You'll also learn how to collect tasks into complete Playbooks to automate server setup from start to finish. The topics that it covers include how to: - Become familiar with configuration management tools and processes, and the benefits of using them to manage your infrastructure. - Install and configure Ansible on an Ubuntu 20.04 control node, ensuring that your servers are properly set up and that you are able to execute remote instructions through Ansible. - Build inventory files and organize your servers into groups to selectively control how and where Ansible commands are run. - Run Ad Hoc commands to execute individual tasks on one, or multiple remote servers. - Package individual commands into Playbooks that you can use to automate the provisioning of m ...
GraphQL in Action
Reduce bandwidth demands on your APIs by getting only the results you need - all in a single request! The GraphQL query language simplifies interactions with web servers, enabling smarter API queries that can hugely improve the efficiency of data requests. In GraphQL in Action, you'll learn how to bring those benefits to your own APIs, giving your clients the power to ask for exactly what they need from your server, no more, no less. Practical and example-driven, this book teaches everything you need to get started with GraphQL - from design principles and syntax right through to performance optimization. GraphQL APIs are fast, efficient, and easy to maintain. They reduce app latency and server cost while boosting developer productivity. This powerful query layer offers precise control over API requests and returns, making apps faster and less prone to error. GraphQL in Action gives you the tools to get comfortable with the GraphQL language, build and optimize a data API service, ...
Reduce bandwidth demands on your APIs by getting only the results you need - all in a single request! The GraphQL query language simplifies interactions with web servers, enabling smarter API queries that can hugely improve the efficiency of data requests. In GraphQL in Action, you'll learn how to bring those benefits to your own APIs, giving your clients the power to ask for exactly what they need from your server, no more, no less. Practical and example-driven, this book teaches everything you need to get started with GraphQL - from design principles and syntax right through to performance optimization. GraphQL APIs are fast, efficient, and easy to maintain. They reduce app latency and server cost while boosting developer productivity. This powerful query layer offers precise control over API requests and returns, making apps faster and less prone to error. GraphQL in Action gives you the tools to get comfortable with the GraphQL language, build and optimize a data API service, ...
React Hooks in Action
Build stylish, slick, and speedy-to-load user interfaces in React without writing custom classes. React Hooks are a new category of functions that help you to manage state, lifecycle, and side effects within functional components. React Hooks in Action teaches you to use pre-built hooks like useState, useReducer and useEffect to build your own hooks. Your code will be more reusable, require less boilerplate, and you'll instantly be a more effective React developer. Get started with React Hooks and you'll soon have code that's better organized and easier to maintain. React Hooks are targeted JavaScript functions that let you reuse and share functionality across components. Use them to split components into smaller functions, manage state and side effects, and access React features without classes - all without having to rearrange your component hierarchy. React Hooks in Action teaches you to write fast and reusable React components using Hooks. You'll start by learning to create c ...
Build stylish, slick, and speedy-to-load user interfaces in React without writing custom classes. React Hooks are a new category of functions that help you to manage state, lifecycle, and side effects within functional components. React Hooks in Action teaches you to use pre-built hooks like useState, useReducer and useEffect to build your own hooks. Your code will be more reusable, require less boilerplate, and you'll instantly be a more effective React developer. Get started with React Hooks and you'll soon have code that's better organized and easier to maintain. React Hooks are targeted JavaScript functions that let you reuse and share functionality across components. Use them to split components into smaller functions, manage state and side effects, and access React features without classes - all without having to rearrange your component hierarchy. React Hooks in Action teaches you to write fast and reusable React components using Hooks. You'll start by learning to create c ...
ASP.NET Core 3.1 Succinctly
ASP.NET Core 3.1 Succinctly specifically covers the web development part of the ASP.NET Core framework, which has gone through some improvements since it was first released. In this updated e-book, Simone Chiaretta Ugo Lattanzi guide readers through the foundations of the library, cover its basic features, and cover the new version of the web application frameworks ASP.NET MVC, Web API, and Blazor. At its end, this book shows you how to deploy applications to the cloud, specifically on Azure. ...
ASP.NET Core 3.1 Succinctly specifically covers the web development part of the ASP.NET Core framework, which has gone through some improvements since it was first released. In this updated e-book, Simone Chiaretta Ugo Lattanzi guide readers through the foundations of the library, cover its basic features, and cover the new version of the web application frameworks ASP.NET MVC, Web API, and Blazor. At its end, this book shows you how to deploy applications to the cloud, specifically on Azure. ...
Hands-On Financial Trading with Python
Algorithmic 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 strat ...
Algorithmic 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 strat ...
Beginning T-SQL, 4th Edition
Get a performance-oriented introduction to the T-SQL language underlying the Microsoft SQL Server and Azure SQL database engines. This fourth edition is updated to include SQL Notebooks as well as up-to-date syntax and features for T-SQL on-premises and in the Azure cloud. Exercises and examples now include the WideWorldImporters database, the newest sample database from Microsoft for SQL Server. Also new in this edition is coverage of JSON from T-SQL, news about performance enhancements called Intelligent Query Processing, and an appendix on running SQL Server in a container on macOS or Linux. Beginning T-SQL starts you on the path to mastering T-SQL with an emphasis on best practices. Using the sound coding techniques taught in this book will lead to excellent performance in the queries that you write in your daily work. Important techniques such as windowing functions are covered to help you write fast-executing queries that solve real business problems.The book begins with an i ...
Get a performance-oriented introduction to the T-SQL language underlying the Microsoft SQL Server and Azure SQL database engines. This fourth edition is updated to include SQL Notebooks as well as up-to-date syntax and features for T-SQL on-premises and in the Azure cloud. Exercises and examples now include the WideWorldImporters database, the newest sample database from Microsoft for SQL Server. Also new in this edition is coverage of JSON from T-SQL, news about performance enhancements called Intelligent Query Processing, and an appendix on running SQL Server in a container on macOS or Linux. Beginning T-SQL starts you on the path to mastering T-SQL with an emphasis on best practices. Using the sound coding techniques taught in this book will lead to excellent performance in the queries that you write in your daily work. Important techniques such as windowing functions are covered to help you write fast-executing queries that solve real business problems.The book begins with an i ...
Convolutional Neural Networks with Swift for Tensorflow
Dive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar and easy to work with Swift language. It begins with a basic machine learning overview and then ramps up to neural networks and convolutions and how they work. Using Swift and Tensorflow, you'll perform data augmentation, build and train large networks, and build networks for mobile devices. You'll also cover cloud training and the network you build can categorize greyscale data, such as mnist, to large scale modern approaches that can categorize large datasets, such as imagenet. Convolutional Neural Networks with Swift for Tensorflow uses a simple approach that adds progressive layers of complexity until you have arrived at the current state of the art for this field. ...
Dive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar and easy to work with Swift language. It begins with a basic machine learning overview and then ramps up to neural networks and convolutions and how they work. Using Swift and Tensorflow, you'll perform data augmentation, build and train large networks, and build networks for mobile devices. You'll also cover cloud training and the network you build can categorize greyscale data, such as mnist, to large scale modern approaches that can categorize large datasets, such as imagenet. Convolutional Neural Networks with Swift for Tensorflow uses a simple approach that adds progressive layers of complexity until you have arrived at the current state of the art for this field. ...
Deep Reinforcement Learning in Unity
Gain an in-depth overview of reinforcement learning for autonomous agents in game development with Unity. This book starts with an introduction to state-based reinforcement learning algorithms involving Markov models, Bellman equations, and writing custom C# code with the aim of contrasting value and policy-based functions in reinforcement learning. Then, you will move on to path finding and navigation meshes in Unity, setting up the ML Agents Toolkit (including how to install and set up ML agents from the GitHub repository), and installing fundamental machine learning libraries and frameworks (such as Tensorflow). You will learn about: deep learning and work through an introduction to Tensorflow for writing neural networks (including perceptron, convolution, and LSTM networks), Q learning with Unity ML agents, and porting trained neural network models in Unity through the Python-C# API. You will also explore the OpenAI Gym Environment used throughout the book. Deep Reinforcement ...
Gain an in-depth overview of reinforcement learning for autonomous agents in game development with Unity. This book starts with an introduction to state-based reinforcement learning algorithms involving Markov models, Bellman equations, and writing custom C# code with the aim of contrasting value and policy-based functions in reinforcement learning. Then, you will move on to path finding and navigation meshes in Unity, setting up the ML Agents Toolkit (including how to install and set up ML agents from the GitHub repository), and installing fundamental machine learning libraries and frameworks (such as Tensorflow). You will learn about: deep learning and work through an introduction to Tensorflow for writing neural networks (including perceptron, convolution, and LSTM networks), Q learning with Unity ML agents, and porting trained neural network models in Unity through the Python-C# API. You will also explore the OpenAI Gym Environment used throughout the book. Deep Reinforcement ...
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 ...