One Meal a Day: The Proper Knowledge of How to Eat to Live Abundantly

One Meal A Day: The Proper Knowledge of How to Eat to Live Abundantly

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Volumul reune?te interviuri din 1997 (Pana mea), 2008 (chat cu scriitori rom?ni – Observator cultural), 2010 (Rom?nia literar?), un chestionar, un dialog inedit (2016) ?i extrase din dou? din documentarele ?n care autoarea a fost prezent? (Aici Nora Iuga ?i Nino al meu). ?n cazul Norei, c?r?ile nu s?nt totul ?i, a?a cum nu avem prea multe exemple literare actuale, omul ?ncununeaz? opera. De-aceea ne-am permis s-o coment?m ?mpreun? ?n dialoguri mai vechi sau mai noi, ?n filme documentare ?i-ntr-un blog audio, pentru a mai trage de timp cu Operele complete. (un cristian)

Bevándorlás Magyarországra, kitelepítés Németországba, málenkij robot Oroszországban, küzdelmes napok újra Magyarországon, a hazában. Világos, Hódmez?vásárhely és Elek. Itt kezd?d?tt családunk élete. 1856-ban született Josef Schwarz anyai dédnagytatám Világoson, katolikus sváb családban. Hódmez?vásárhely az apai ág születési helye. Kerekes Sándor nagyapám 1871-ben született katolikus magyar családban.A sváb parasztok Eleken találkoztak a magyar iparosokkal. Itt találták meg a munkalehet?séget, amivel családjukat el tudták tartani.Családunk t?rténete egyszer? hétk?znapi emberek életér?l szól, akik átéltek két világháborút, ukrajnai kényszermunkát és németországi kitelepítést. Unokáim családunk leszármazottainak ?t?dik generációja. Tudniuk kell, hogy a t?bb mint 150 év alatt családunk t?rténete hogyan alakult, milyen életet éltek ük- és dédszüleik.Elégtételt kell kapnia a nagyszüleimnek és a szüleimnek, hogy az emlékezet nem engedi elfelejteni az életüket.

Exploit design, deployment, and management of large-scale containers About This Book ? Explore the latest features available in Kubernetes 1.10 ? Ensure that your clusters are always available, scalable, and up to date ? Master the skills of designing and deploying large clusters on various cloud platforms Who This Book Is For Mastering Kubernetes is for you if you are a system administrator or a developer who has an intermediate understanding of Kubernetes and wish to master its advanced features. Basic knowledge of networking would also be helpful. In all, this advanced-level book provides a smooth pathway to mastering Kubernetes. What You Will Learn ? Architect a robust Kubernetes cluster for long-time operation ? Discover the advantages of running Kubernetes on GCE, AWS, Azure, and bare metal ? Understand the identity model of Kubernetes, along with the options for cluster federation ? Monitor and troubleshoot Kubernetes clusters and run a highly available Kubernetes ? Create and configure custom Kubernetes resources and use third-party resources in your automation workflows ? Enjoy the art of running complex stateful applications in your container environment ? Deliver applications as standard packages In Detail Kubernetes is an open source system that is used to automate the deployment, scaling, and management of containerized applications. If you are running more containers or want automated management of your containers, you need Kubernetes at your disposal. To put things into perspective, Mastering Kubernetes walks you through the advanced management of Kubernetes clusters. To start with, you will learn the fundamentals of both Kubernetes architecture and Kubernetes design in detail. You will discover how to run complex stateful microservices on Kubernetes including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backend. Using real-world use cases, you will explore the options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you will get to grips with custom resource development and utilization in automation and maintenance workflows. To scale up your knowledge of Kubernetes, you will encounter some additional concepts based on the Kubernetes 1.10 release, such as Promethus, Role-based access control, API aggregation, and more. By the end of this book, you’ll know everything you need to graduate from intermediate to advanced level of understanding Kubernetes. Style and approach Delving into the design of the Kubernetes platform, the reader will be exposed to Kubernetes advanced features and best practices. This advanced-level book will provide a pathway to mastering Kubernetes.

Over 79 hands-on recipes for professional embedded Linux developers to optimize and boost their Yocto Project know-how About This Book ? Optimize your Yocto setup to speed up development and debug build issues ? Use what is quickly becoming the standard embedded Linux product builder framework—the Yocto Project ? Recipe-based implementation of best practices to optimize your Linux system Who This Book Is For If you are an embedded Linux developer with the basic knowledge of Yocto Project, this book is an ideal way to broaden your knowledge with recipes for embedded development. What You Will Learn ? Optimize your Yocto Project setup to speed up development and debug build issues ? Use Docker containers to build Yocto Project-based systems ? Take advantage of the user-friendly Toaster web interface to the Yocto Project build system ? Build and debug the Linux kernel and its device trees ? Customize your root filesystem with already-supported and new Yocto packages ? Optimize your production systems by reducing the size of both the Linux kernel and root filesystems ? Explore the mechanisms to increase the root filesystem security ? Understand the open source licensing requirements and how to comply with them when cohabiting with proprietary programs ? Create recipes, and build and run applications in C, C++, Python, Node.js, and Java In Detail The Yocto Project has become the de facto distribution build framework for reliable and robust embedded systems with a reduced time to market. You'll get started by working on a build system where you set up Yocto, create a build directory, and learn how to debug it. Then, you'll explore everything about the BSP layer, from creating a custom layer to debugging device tree issues. In addition to this, you’ll learn how to add a new software layer, packages, data, *s, and configuration files to your system. You will then cover topics based on application development, such as using the Software Development Kit and how to use the Yocto project in various development environments. Toward the end, you will learn how to debug, trace, and profile a running system. This second edition has been updated to include new content based on the latest Yocto release. Style and approach This recipe-based book will guide you through all the development stages of an embedded Linux product design using the Yocto Project.

Get command of your organizational Big Data using the power of data science and analytics About This Book ? A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions ? Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses ? Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Who This Book Is For The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience. What You Will Learn ? Get a 360-degree view into the world of Big Data, data science and machine learning ? Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives ? Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R ? Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions ? Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications ? Understand corporate strategies for successful Big Data and data science projects ? Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies In Detail Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. Style and approach This book equips you with a knowledge of various NoSQL tools, R, Python programming, cloud platforms, and techniques so you can use them to store, analyze, and deliver meaningful insights from your data.

Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV. About This Book ? Learn how to apply complex visual effects to images with OpenCV 3.x and Python ? Extract features from an image and use them to develop advanced applications ? Build algorithms to help you understand image content and perform visual searches ? Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented reality Who This Book Is For This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. What You Will Learn ? Detect shapes and edges from images and videos ? How to apply filters on images and videos ? Use different techniques to manipulate and improve images ? Extract and manipulate particular parts of images and videos ? Track objects or colors from videos ? Recognize specific object or faces from images and videos ? How to create Augmented Reality applications ? Apply artificial neural networks and machine learning to improve object recognition In Detail Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications. Style and approach The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation.

Transform yourself into a Kubernetes specialist in serverless applications. About This Book ? Get hands-on experience in installing, configuring, and using services such as Kubeless, Funktion, OpenWhisk, and Fission ? Learn how to launch Kubernetes both locally and in public clouds ? Explore the differences between using services such as AWS Lambda and Azure Functions and running your own Who This Book Is For If you are a DevOps engineer, cloud architect, or a stakeholder keen to learn about serverless functions in Kubernetes environments, then this book is for you. What You Will Learn ? Get a detailed analysis of serverless/Functions as a Service ? Get hands-on with installing and running tasks in Kubernetes using Minikube ? Install Kubeless locally and launch your first function. ? Launch Kubernetes in the cloud and move your applications between your local machine and your cloud cluster ? Deploy applications on Kubernetes using Apache OpenWhisk ? Explore topics such as Funktion and Fission installation on the cloud followed by launching applications ? Monitor a serverless function and master security best practices and Kubernetes use cases In Detail Kubernetes has established itself as the standard platform for container management, orchestration, and deployment. It has been adopted by companies such as Google, its original developers, and Microsoft as an integral part of their public cloud platforms, so that you can develop for Kubernetes and not worry about being locked into a single vendor. This book will initially start by introducing serverless functions. Then you will configure tools such as Minikube to run Kubernetes. Once you are up-and-running, you will install and configure Kubeless, your first step towards running Function as a Service (FaaS) on Kubernetes. Then you will gradually move towards running Fission, a framework used for managing serverless functions on Kubernetes environments. Towards the end of the book, you will also work with Kubernetes functions on public and private clouds. By the end of this book, we will have mastered using Function as a Service on Kubernetes environments. Style and approach A clear, concise, and straightforward book that will empower you work with clusters and run serverless functions effectively.

Deploy and manage VMware vSphere 6.5 components with ease. About This Book ? Simplified and to-the-point theory and practical recipes to deploy and manage vSphere 6.5 ? Discover the best ways to deploy stateless and stateful ESXi hosts and upgrade them ? Storage and network resource management ? Certificate management using VMCA ? Monitor the performance of a vSphere environment. Who This Book Is For If you are a system administrator, support professional, or anyone interested in learning how to install, configure, and manage a vSphere environment, then this book is for you. This task-oriented reference guide will also benefit consultants or infrastructure architects who design and deploy vSphere 6.5 environments. What You Will Learn ? Upgrade your existing vSphere environment or perform a fresh deployment. ? Automate the deployment and management of large sets of ESXi hosts in your vSphere Environment ? Configure and manage FC, iSCSI, and NAS storage, and get more control over how storage resources are allocated and managed ? Configure vSphere networking by deploying host-wide and data center-wide switches in your vSphere environment ? Configure high availability on a host cluster and learn how to enable the fair distribution and utilization of compute resources ? Patch and upgrade the vSphere environment ? Handle certificate request generation and renew component certificates ? Monitor performance of a vSphere environment In Detail VMware vSphere is a complete and robust virtualization product suite that helps transform data centers into simplified on-premises cloud infrastructures, providing for the automation and orchestration of workload deployment and life cycle management of the infrastructure. This book focuses on the latest release of VMware vSphere and follows a recipe-based approach, giving you hands-on instructions required to deploy and manage a vSphere environment. The book starts with the procedures involved in upgrading your existing vSphere infrastructure to vSphere 6.5, followed by deploying a new vSphere 6.5 environment. Then the book delves further into the procedures involved in managing storage and network access to the ESXi hosts and the virtual machines running on them. Moving on, the book covers high availability and fair distribution/utilization of clustered compute and storage resources. Finally, the book covers patching and upgrading the vSphere infrastructure using VUM, certificate management using VMCA, and finishes with a chapter covering the tools that can be used to monitor the performance of a vSphere infrastructure. Style and approach This book will quickly get you started with managing VMware components.

Make the most of Kotlin by leveraging design patterns and best practices to build scalable and high performing apps About This Book ? Understand traditional GOF design patterns to apply generic solutions ? Shift from OOP to FP; covering reactive and concurrent patterns in a step-by-step manner ? Choose the best microservices architecture and MVC for your development environment Who This Book Is For This book is for developers who would like to master design patterns with Kotlin to build efficient and scalable applications. Basic Java or Kotlin programming knowledge is assumed What You Will Learn ? Get to grips with Kotlin principles, including its strengths and weaknesses ? Understand classical design patterns in Kotlin ? Explore functional programming using built-in features of Kotlin ? Solve real-world problems using reactive and concurrent design patterns ? Use threads and coroutines to simplify concurrent code flow ? Understand antipatterns to write clean Kotlin code, avoiding common pitfalls ? Learn about the design considerations necessary while choosing between architectures In Detail Design patterns enable you as a developer to speed up the development process by providing you with proven development paradigms. Reusing design patterns helps prevent complex issues that can cause major problems, improves your code base, promotes code reuse, and makes an architecture more robust. The mission of this book is to ease the adoption of design patterns in Kotlin and provide good practices for programmers. The book begins by showing you the practical aspects of smarter coding in Kotlin, explaining the basic Kotlin syntax and the impact of design patterns. From there, the book provides an in-depth explanation of the classical design patterns of creational, structural, and behavioral families, before heading into functional programming. It then takes you through reactive and concurrent patterns, teaching you about using streams, threads, and coroutines to write better code along the way By the end of the book, you will be able to efficiently address common problems faced while developing applications and be comfortable working on scalable and maintainable projects of any size. Style and approach This book explains design patterns in a step-by-step manner with clear and concise code examples

Learn how to implement the reactive programming paradigm with C++ and build asynchronous and concurrent applications About This Book ? Efficiently exploit concurrency and parallelism in your programs ? Use the Functional Reactive programming model to structure programs ? Understand reactive GUI programming to make your own applications using Qt Who This Book Is For If you’re a C++ developer interested in using reactive programming to build asynchronous and concurrent applications, you’ll find this book extremely useful. This book doesn’t assume any previous knowledge of reactive programming. What You Will Learn ? Understand language-level concurrency in C++ ? Explore advanced C++ programming for the FRP ? Uncover the RxCpp library and its programming model ? Mix the FP and OOP constructs in C++ 17 to write well-structured programs ? Master reactive microservices in C++ ? Create custom operators for RxCpp ? Learn advanced stream processing and error handling In Detail Reactive programming is an effective way to build highly responsive applications with an easy-to-maintain code base. This book covers the essential functional reactive concepts that will help you build highly concurrent, event-driven, and asynchronous applications in a simpler and less error-prone way. C++ Reactive Programming begins with a discussion on how event processing was undertaken by different programming systems earlier. After a brisk introduction to modern C++ (C++17), you’ll be taken through language-level concurrency and the lock-free programming model to set the stage for our foray into the Functional Programming model. Following this, you’ll be introduced to RxCpp and its programming model. You’ll be able to gain deep insights into the RxCpp library, which facilitates reactive programming. You’ll learn how to deal with reactive programming using Qt/C++ (for the desktop) and C++ microservices for the Web. By the end of the book, you will be well versed with advanced reactive programming concepts in modern C++ (C++17). Style and approach The book includes real-world problems that you will solve with the reactive programming model. It highlights the way event processing has evolved in the programming world.

Build fast, scalable, and high performing applications with Delphi About This Book ? Build efficient and concurrent applications in Delphi with focused examples ? Identify performance bottlenecks and apply the correct algorithm to increase the performance of applications. ? Delve into parallel programming and memory management to optimize your code Who This Book Is For This book is for Delphi developers who would like to build high performance applications with Delphi. Prior knowledge of Delphi is assumed. What You Will Learn ? Find performance bottlenecks and easily mitigate them ? Discover different approaches to fix algorithms ? Understand parallel programming and work with various tools included with Delphi ? Master the RTL for code optimization ? Explore memory managers and their implementation ? Leverage external libraries to write better performing programs In Detail Delphi is a cross-platform Integrated Development Environment (IDE) that supports rapid application development for Microsoft Windows, Apple Mac OS X, Google Android, iOS, and now Linux with RAD Studio 10.2. This book will be your guide to build efficient high performance applications with Delphi. The book begins by explaining how to find performance bottlenecks and apply the correct algorithm to fix them. It will teach you how to improve your algorithms before taking you through parallel programming. You’ll then explore various tools to build highly concurrent applications. After that, you’ll delve into improving the performance of your code and master cross-platform RTL improvements. Finally, we’ll go through memory management with Delphi and you’ll see how to leverage several external libraries to write better performing programs. By the end of the book, you’ll have the knowledge to create high performance applications with Delphi. Style and approach This book will take a step-by-step approach with focused examples to teach you how to increase the performance of applications.

Take your application development skills to the next level by implementing Spring Boot features effectively About This Book ? This collection of effective recipes serves as guidelines for Spring Boot application development ? Get up to date with features of the latest version of Spring Boot 2.0 ? Tips and tricks to improve your efficiency through the stages of software development Who This Book Is For This book is for Java Developers who have good knowledge and understanding of Spring and Java application development. What You Will Learn ? Get to know Spring Boot Starters and create custom auto-configurations ? Work with custom annotations that enable bean activation ? Use DevTools to easily develop and debug applications ? Learn the effective testing techniques by integrating Cucumber and Spock ? Observe an eternal application configuration using Consul ? Move your existing Spring Boot applications to the cloud ? Use Hashicorp Consul and Netflix Eureka for dynamic Service Discovery ? Understand the various mechanisms that Spring Boot provides to examine an application’s health In Detail The Spring framework provides great flexibility for Java development, which also results in tedious configuration work. Spring Boot addresses the configuration difficulties of Spring and makes it easy to create standalone, production-grade Spring-based applications. This practical guide makes the existing development process more efficient. Spring Boot Cookbook 2.0 Second Edition smartly combines all the skills and expertise to efficiently develop, test, deploy, and monitor applications using Spring Boot on premise and in the cloud. We start with an overview of the important Spring Boot features you will learn to create a web application for a RESTful service. Learn to fine-tune the behavior of a web application by learning about custom routes and asset paths and how to modify routing patterns. Address the requirements of a complex enterprise application and cover the creation of custom Spring Boot starters. This book also includes examples of the new and improved facilities available to create various kinds of tests introduced in Spring Boot 1.4 and 2.0, and gain insights into Spring Boot DevTools. Explore the basics of Spring Boot Cloud modules and various Cloud starters to make applications in “Cloud Native” and take advantage of Service Discovery and Circuit Breakers. Style and approach This practical guide follows a recipe-based approach and provides extremely helpful guidelines to build, configure, and customize your Spring Boot applications.

A highly detailed guide to performing powerful attack vectors in many hands-on scenarios and defending significant security flaws in your company's infrastructure About This Book ? Advanced exploitation techniques to breach modern operating systems and complex network devices ? Learn about Docker breakouts, Active Directory delegation, and CRON jobs ? Practical use cases to deliver an intelligent endpoint-protected system Who This Book Is For If you are a system administrator, SOC analyst, penetration tester, or a network engineer and want to take your penetration testing skills and security knowledge to the next level, then this book is for you. Some prior experience with penetration testing tools and knowledge of Linux and Windows command-line syntax is beneficial. What You Will Learn ? Exposure to advanced infrastructure penetration testing techniques and methodologies ? Gain hands-on experience of penetration testing in Linux system vulnerabilities and memory exploitation ? Understand what it takes to break into enterprise networks ? Learn to secure the configuration management environment and continuous delivery pipeline ? Gain an understanding of how to exploit networks and IoT devices ? Discover real-world, post-exploitation techniques and countermeasures In Detail It has always been difficult to gain hands-on experience and a comprehensive understanding of advanced penetration testing techniques and vulnerability assessment and management. This book will be your one-stop solution to compromising complex network devices and modern operating systems. This book provides you with advanced penetration testing techniques that will help you exploit databases, web and application servers, switches or routers, Docker, VLAN, VoIP, and VPN. With this book, you will explore exploitation abilities such as offensive PowerShell tools and techniques, CI servers, database exploitation, Active Directory delegation, kernel exploits, cron jobs, VLAN hopping, and Docker breakouts. Moving on, this book will not only walk you through managing vulnerabilities, but will also teach you how to ensure endpoint protection. Toward the end of this book, you will also discover post-exploitation tips, tools, and methodologies to help your organization build an intelligent security system. By the end of this book, you will have mastered the skills and methodologies needed to breach infrastructures and provide complete endpoint protection for your system. Style and approach Your one-stop guide to mastering the skills and methodologies of breaching infrastructures and providing complete endpoint protection to your system.

Learn continuous deployment and automation with code-signing, continuous testing, building, deploying, and releasing of your app. About This Book ? A practical guide on automating your mobile development pipeline with Fastlane, Jenkins, and Slack. ? Build, test, run and deploy your mobile application release with this end to end guide. ? Implement Continuous Integration, delivery, and deployment practices to optimize your application development workflow for faster and efficient release builds. Who This Book Is For This book is intended for mobile developers who are keen on incorporating Continuous integration and deployment practices in their workflow. What You Will Learn ? Harness the fastlane tools for the Continuous Deployment strategy ? Integrate Continuous Deployment with existing Continuous Integration. ? Automate upload of screenshots across all device screen-sizes ? Manage push notifications, provisioning profiles, and code-signing certificates ? Orchestrate automated build and deployments of new versions of your app ? Regulate your TestFlight users and on-board new testers In Detail Competitive mobile apps depend strongly on the development team’s ability to deliver successful releases, consistently and often. Although continuous integration took a more mainstream priority among the development industry, companies are starting to realize the importance of continuity beyond integration and testing. This book starts off with a brief introduction to fastlane—a robust command-line tool that enables iOS and Android developers to automate their releasing workflow. The book then explores and guides you through all of its features and utilities; it provides the reader a comprehensive understanding of the tool and how to implement them. Themes include setting up and managing your certificates and provisioning and push notification profiles; automating the creation of apps and managing the app metadata on iTunes Connect and the Apple Developer Portal; and building, distributing and publishing your apps to the App Store. You will also learn how to automate the generation of localized screenshots and mesh your continuous delivery workflow into a continuous integration workflow for a more robust setup. By the end of the book, you will gain substantial knowledge on delivering bug free, developer-independent, and stable application release cycle. Style and approach A step by step guide taking the readers through all the tools of fastlane.

Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key Features *A step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZ *A modern, practical and computational approach to Bayesian statistical modeling *A tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises. Book Description The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models. The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others. By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After reading the book you will be better prepared to delve into more advanced material or specialized statistical modeling if you need to. What you will learn *Build probabilistic models using the Python library PyMC3 *Analyze probabilistic models with the help of ArviZ *Acquire the skills required to sanity check models and modify them if necessary *Understand the advantages and caveats of hierarchical models *Find out how different models can be used to answer different data analysis questions *Compare models and choose between alternative ones *Discover how different models are unified from a probabilistic perspective *Think probabilistically and benefit from the flexibility of the Bayesian framework Who this book is for If you are a student, data scientist, researcher, or a developer looking to get started with Bayesian data analysis and probabilistic programming, this book is for you. The book is introductory so no previous statistical knowledge is required, although some experience in using Python and NumPy is expected.

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features *Implement machine learning algorithms to build, train, and validate algorithmic models *Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions *Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You’ll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn *Implement machine learning techniques to solve investment and trading problems *Leverage market, fundamental, and alternative data to research alpha factors *Design and fine-tune supervised, unsupervised, and reinforcement learning models *Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn *Integrate machine learning models into a live trading strategy on Quantopian *Evaluate strategies using reliable backtesting methodologies for time series *Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow *Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.

Speed up the design and implementation of deep learning solutions using Apache Spark Key Features * Explore the world of distributed deep learning with Apache Spark * Train neural networks with deep learning libraries such as BigDL and TensorFlow * Develop Spark deep learning applications to intelligently handle large and complex datasets Book Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learn * Understand the basics of deep learning * Set up Apache Spark for deep learning * Understand the principles of distribution modeling and different types of neural networks * Obtain an understanding of deep learning algorithms * Discover textual analysis and deep learning with Spark * Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras * Explore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.

Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Key Features * Get to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and Keras * Implement advanced concepts and popular machine learning algorithms in real-world projects * Build analytics, computer vision, and neural network projects Book Description Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects. What you will learn * Understand the Python data science stack and commonly used algorithms * Build a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window * Understand NLP concepts by creating a custom news feed * Create applications that will recommend GitHub repositories based on ones you’ve starred, watched, or forked * Gain the skills to build a chatbot from scratch using PySpark * Develop a market-prediction app using stock data * Delve into advanced concepts such as computer vision, neural networks, and deep learning Who this book is for This book is for machine learning practitioners, data scientists, and deep learning enthusiasts who want to take their machine learning skills to the next level by building real-world projects. The intermediate-level guide will help you to implement libraries from the Python ecosystem to build a variety of projects addressing various machine learning domains. Knowledge of Python programming and machine learning concepts will be helpful.