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Quantum Machine Learning with Python
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, ...
PHP 8 Objects, Patterns, and Practice
PHP 8 Objects, Patterns, and Practice

Learn how to develop elegant and rock-solid systems using PHP, aided by three key elements: object fundamentals, design principles, and best practices. The 6th edition of this popular book has been fully updated for PHP 8, including attributes, constructor property promotion, new argument and return pseudo-types, and more. It also covers many features new since the last edition including typed properties, the null coalescing operator, and void return types. This book provides a solid grounding in PHP's support for objects, it builds on this foundation to instill core principles of software design and then covers the tools and practices needed to develop, test, and deploy robust code. PHP 8 Objects, Patterns, and Practice begins by covering PHP's object-oriented features. It introduces key topics including class declarations, inheritance, and reflection. The next section is devoted to design patterns. It explains the principles that make patterns powerful. You'll cover many of the cl ...
How To Manage Remote Servers with Ansible
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 ...
Chaos Engineering
Chaos Engineering

Auto engineers test the safety of a car by intentionally crashing it and carefully observing the results. Chaos engineering applies the same principles to software systems. In Chaos Engineering: Site reliability through controlled disruption, you'll learn to run your applications and infrastructure through a series of tests that simulate real-life failures. You'll maximize the benefits of chaos engineering by learning to think like a chaos engineer, and how to design the proper experiments to ensure the reliability of your software. With examples that cover a whole spectrum of software, you'll be ready to run an intensive testing regime on anything from a simple WordPress site to a massive distributed system running on Kubernetes. Can your network survive a devastating failure? Could an accident bring your day-to-day operations to a halt? Chaos engineering simulates infrastructure outages, component crashes, and other calamities to show how systems and staff respond. Testing systems ...
GitOps and Kubernetes
GitOps and Kubernetes

GitOps and Kubernetes introduces a radical idea - managing your infrastructure with the same Git pull requests you use to manage your codebase. In this in-depth tutorial, you'll learn to operate infrastructures based on powerful-but-complex technologies such as Kubernetes with the same Git version control tools most developers use daily. With these GitOps techniques and best practices, you'll accelerate application development without compromising on security, easily roll back infrastructure changes, and seamlessly introduce new team members to your automation process. With GitOps you use the Git version control system to organize and manage your infrastructure just like any other codebase. It's an excellent model for applications deployed as containers and pods on Kubernetes. GitOps and Kubernetes teaches you how to use Git and the GitOps methodology to manage a Kubernetes cluster. The book interleaves theory with practice, presenting core Ops concepts alongside easy-to-implemen ...
Data Pipelines with Apache Airflow
Data Pipelines with Apache Airflow

A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, keeping every process along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, Data Pipelines with Apache Airflow teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack. Data pipelines manage the flow of data from initial collection through consolidation, cleaning, analysis, visualization, and more. Apache Airflow provides a single platform you can use to design, implement, monitor, and maintain your pipelines. Its easy-to-use UI, plug-and-play options, and flexible Python scripting make Airflow perfect for any data management task. Data Pipelines with Apache Airflow teaches you how to build an ...
Generative AI with Python and TensorFlow 2
Generative AI with Python and TensorFlow 2

In recent years, generative artificial intelligence has been instrumental in the creation of lifelike data (images, speech, video, music, and text) from scratch. In this book you will unpack how these powerful models are created from relatively simple building blocks, and how you might adapt these models to your own use cases. You will begin by setting up clean containerized environments for Python and getting to grips with the fundamentals of deep neural networks, learning about core concepts like the perceptron, activation functions, backpropagation, and how they all tie together. Once you have covered the basics, you will explore deep generative models in depth, including OpenAI's GPT-series of news generators, networks for style transfer and deepfakes, and synergy with reinforcement learning. As you progress, you will focus on abstractions where useful, and understand the "nuts and bolts" of how the models are composed in code, underpinned by detailed architecture diagrams. T ...
Hands-On Financial Trading with Python
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 ...
Convolutional Neural Networks with Swift for Tensorflow
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. ...
Deep Reinforcement Learning in Unity
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 ...
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