Leverage the power of Python and statistical modeling techniques for building accurate predictive models Key Features * Get introduced to Python's rich suite of libraries for statistical modeling * Implement regression, clustering and train neural networks from scratch * Includes real-world examples on training end-to-end machine learning systems in Python Book Description Python's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today. Its rich libraries are widely used for data analysis, and more importantly, for building state-of-the-art predictive models. This book takes you through an exciting journey, of using these libraries to implement effective statistical models for predictive analytics. You’ll start by diving into classical statistical analysis, where you will learn to compute descriptive statistics using pandas. You will look at supervised learning, where you will explore the principles of machine learning and train different machine learning models from scratch. You will also work with binary prediction models, such as data classification using k-nearest neighbors, decision trees, and random forests. This book also covers algorithms for regression analysis, such as ridge and lasso regression, and their implementation in Python. You will also learn how neural networks can be trained and deployed for more accurate predictions, and which Python libraries can be used to implement them. By the end of this book, you will have all the knowledge you need to design, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive analytics. What you will learn * Understand the importance of statistical modeling * Learn about the various Python packages for statistical analysis * Implement algorithms such as Naive Bayes, random forests, and more * Build predictive models from scratch using Python's scikit-learn library * Implement regression analysis and clustering * Learn how to train a neural network in Python Who this book is for If you are a data scientist, a statistician or a machine learning developer looking to train and deploy effective machine learning models using popular statistical techniques, then this book is for you. Knowledge of Python programming is required to get the most out of this book.

Make use of hands-on recipes for many tasks that are typically encountered in both the on-premises as well as the cloud world. Key Features * A recipe-based guide to help you build effective administrative solutions * Gain hands-on experience with the newly added features of PowerShell Core * Manage critical business environments with professional scripting practices Book Description This book will follow a recipe-based approach and start off with an introduction to the fundamentals of PowerShell, and explaining how to install and run it through simple examples. Next, you will learn how to use PowerShell to access and manipulate data and how to work with different streams as well. You will also explore the object model which will help with regard to PowerShell function deployment. Going forward, you will get familiar with the pipeline in its different use cases. The next set of chapters will deal with the different ways of accessing data in PowerShell. You will also learn to automate various tasks in Windows and Linux using PowerShell Core, as well as explore Windows Server. Later, you will be introduced to Remoting in PowerShell Core and Just Enough Administration concept. The last set of chapters will help you understand the management of a private and public cloud with PowerShell Core. You will also learn how to access web services and explore the high-performance scripting methods. By the end of this book, you will gain the skills to manage complex tasks effectively along with increasing the performance of your environment. What you will learn * Leverage cross-platform interaction with systems * Make use of the PowerShell recipes for frequent tasks * Get a better understanding of the inner workings of PowerShell * Understand the compatibility of built-in Windows modules with PowerShell Core * Learn best practices associated with PowerShell scripting * Avoid common pitfalls and mistakes Who this book is for This book will be for windows administrators who want to enhance their PowerShell scripting skills to the next level. System administrators wanting to automate common to complex tasks with PowerShell scripts would benefit from this book. Prior understanding on PowerShell would be necessary.

A problem-solution guide to encounter various NLP tasks utilizing Java open source libraries and cloud-based solutions Key Features * Perform simple-to-complex NLP text processing tasks using modern Java libraries Extract relationships between different text complexities using a problem-solution approach * Utilize cloud-based APIs to perform machine translation operations Book Description Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon’s AWS. You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentences, or semantic words. What you will learn * Explore how to use tokenizers in NLP processing * Implement NLP techniques in machine learning and deep learning applications * Identify sentences within the text and learn how to train specialized NER models * Learn how to classify documents and perform sentiment analysis * Find semantic similarities between text elements and extract text from a variety of sources * Preprocess text from a variety of data sources * Learn how to identify and translate languages Who this book is for This book is for data scientists, NLP engineers, and machine learning developers who want to perform their work on linguistic applications faster with the use of popular libraries on JVM machines. This book will help you build real-world NLP applications using a recipe-based approach. Prior knowledge of Natural Language Processing basics and Java programming is expected.

Build Prometheus ecosystems with metric-centric visualization, alerting, and querying Key Features * Integrate Prometheus with Alertmanager and Grafana for building a complete monitoring system * Explore PromQL, Prometheus' functional query language, with easy-to-follow examples * Learn how to deploy Prometheus components using Kubernetes and traditional instances Book Description Prometheus is an open source monitoring system. It provides a modern time series database, a robust query language, several metric visualization possibilities, and a reliable alerting solution for traditional and cloud-native infrastructure. This book covers the fundamental concepts of monitoring and explores Prometheus architecture, its data model, and how metric aggregation works. Multiple test environments are included to help explore different configuration scenarios, such as the use of various exporters and integrations. You’ll delve into PromQL, supported by several examples, and then apply that knowledge to alerting and recording rules, as well as how to test them. After that, alert routing with Alertmanager and creating visualizations with Grafana is thoroughly covered. In addition, this book covers several service discovery mechanisms and even provides an example of how to create your own. Finally, you’ll learn about Prometheus federation, cross-sharding aggregation, and also long-term storage with the help of Thanos. By the end of this book, you’ll be able to implement and scale Prometheus as a full monitoring system on-premises, in cloud environments, in standalone instances, or using container orchestration with Kubernetes. What you will learn * Grasp monitoring fundamentals and implement them using Prometheus * Discover how to extract metrics from common infrastructure services * Find out how to take full advantage of PromQL * Design a highly available, resilient, and scalable Prometheus stack * Explore the power of Kubernetes Prometheus Operator * Understand concepts such as federation and cross-shard aggregation * Unlock seamless global views and long-term retention in cloud-native apps with Thanos Who this book is for If you’re a software developer, cloud administrator, site reliability engineer, DevOps enthusiast or system admin looking to set up a fail-safe monitoring and alerting system for sustaining infrastructure security and performance, this book is for you. Basic networking and infrastructure monitoring knowledge will help you understand the concepts covered in this book.

Explore the aspects of financial modeling with the help of clear and easy-to-follow instructions and a variety of Excel features, functions, and productivity tips Key Features * A non data professionals guide to exploring Excel's financial functions and pivot tables * Learn to prepare various models for income and cash flow statements, and balance sheets * Learn to perform valuations and identify growth drivers with real-world case studies Book Description Financial modeling is a core skill required by anyone who wants to build a career in finance. Hands-On Financial Modeling with Microsoft Excel 2019 examines various definitions and relates them to the key features of financial modeling with the help of Excel. This book will help you understand financial modeling concepts using Excel, and provides you with an overview of the steps you should follow to build an integrated financial model. You will explore the design principles, functions, and techniques of building models in a practical manner. Starting with the key concepts of Excel, such as formulas and functions, you will learn about referencing frameworks and other advanced components of Excel for building financial models. Later chapters will help you understand your financial projects, build assumptions, and analyze historical data to develop data-driven models and functional growth drivers. The book takes an intuitive approach to model testing, along with best practices and practical use cases. By the end of this book, you will have examined the data from various use cases, and you will have the skills you need to build financial models to extract the information required to make informed business decisions. What you will learn * Identify the growth drivers derived from processing historical data in Excel * Use discounted cash flow (DCF) for efficient investment analysis * Build a financial model by projecting balance sheets, profit, and loss * Apply a Monte Carlo simulation to derive key assumptions for your financial model * Prepare detailed asset and debt schedule models in Excel * Discover the latest and advanced features of Excel 2019 * Calculate profitability ratios using various profit parameters Who this book is for This book is for data professionals, analysts, traders, business owners, and students, who want to implement and develop a high in-demand skill of financial modeling in their finance, analysis, trading, and valuation work. This book will also help individuals that have and don't have any experience in data and stats, to get started with building financial models. The book assumes working knowledge with Excel.

Your one-stop guide to learning and implementing artificial neural networks with Keras effectively Key Features * Design and create neural network architectures on different domains using Keras * Integrate neural network models in your applications using this highly practical guide * Get ready for the future of neural networks through transfer learning and predicting multi network models Book Description Neural networks are used to solve a wide range of problems in different areas of AI and deep learning. Hands-On Neural Networks with Keras will start with teaching you about the core concepts of neural networks. You will delve into combining different neural network models and work with real-world use cases, including computer vision, natural language understanding, synthetic data generation, and many more. Moving on, you will become well versed with convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, autoencoders, and generative adversarial networks (GANs) using real-world training datasets. We will examine how to use CNNs for image recognition, how to use reinforcement learning agents, and many more. We will dive into the specific architectures of various networks and then implement each of them in a hands-on manner using industry-grade frameworks. By the end of this book, you will be highly familiar with all prominent deep learning models and frameworks, and the options you have when applying deep learning to real-world scenarios and embedding artificial intelligence as the core fabric of your organization. What you will learn * Understand the fundamental nature and workflow of predictive data modeling * Explore how different types of visual and linguistic signals are processed by neural networks * Dive into the mathematical and statistical ideas behind how networks learn from data * Design and implement various neural networks such as CNNs, LSTMs, and GANs * Use different architectures to tackle cognitive tasks and embed intelligence in systems * Learn how to generate synthetic data and use augmentation strategies to improve your models * Stay on top of the latest academic and commercial developments in the field of AI Who this book is for This book is for machine learning practitioners, deep learning researchers and AI enthusiasts who are looking to get well versed with different neural network architecture using Keras. Working knowledge of Python programming language is mandatory.

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features * Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python * Apply machine learning and deep learning techniques with TensorFlow, Keras, and PyTorch * Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn * Handle files and images, and explore various image processing techniques * Explore image transformations, including translation, resizing, and cropping * Gain insights into building histograms * Brush up on contour detection, filtering, and drawing * Work with Augmented Reality to build marker-based and markerless applications * Work with the main machine learning algorithms in OpenCV * Explore the deep learning Python libraries and OpenCV deep learning capabilities * Create computer vision and deep learning web applications Who this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.

Unlock the power of the MEAN stack by creating attractive and real-world projectsAbout This Book·Build six optimum end-to-end web applications using the M.E.A.N stack·Follow the advanced Angular.js 2 application structure to build more scalable and maintainable apps·Integrate an authorization system into your application and reuse existing code from projectsWho This Book Is ForIf you are a web developer with a basic understanding of the MEAN stack, experience in developing applications with JavaScript, and basic experience with NoSQL databases, then this book is for you.What You Will Learn·Build modern, end-to-end web applications by employing the full stack web development solution of MEAN·Learn NoSQL databases and separate the client logic from the server code·Build a complex application from start to finish and work with monetary data in MongoDB·Handle a multi-user type system and authorize your users to access control list·Implement a chat application from scratch using Socket.IO·Create distributed applications and use the power of server-side rendering in your applications·Extend a project with a real-time bidding system using WebSocketsIn DetailThe MEAN stack is a combination of the most popular web development frameworks available—MongoDB, Angular, Express, and Node.js used together to offer a powerful and comprehensive full stack web development solution. It is the modern day web dev alternative to the old LAMP stack. It works by allowing AngularJS to handle the front end, and selecting Mongo, Express, and Node to handle the back-end development, which makes increasing sense to forward-thinking web developers. The MEAN stack is great if you want to prototype complex web applications.This book will enable you to build a better foundation for your AngularJS apps. Each chapter covers a complete, single, advanced end-to-end project. You'll learn how to build complex real-life applications with the MEAN stack and few more advanced projects. You will become familiar with WebSockets and build real-time web applications, as well as create auto-destructing entities. Later, we will combine server-side rendering techniques with a single page application approach. You'll build a fun project and see how to work with monetary data in Mongo. You will also find out how to a build real-time e-commerce application.By the end of this book, you will be a lot more confident in developing real-time, complex web applications using the MEAN stack.Style and approachThis book is filled with independent hands-on projects that teach you how to build real-life end-to-end complex web applications using the MEAN stack.

A fast-paced guide to get you up and running with Swift 3 and its new featuresAbout This Book·Get up to date with the latest changes to Swift 3·Make your life easier by knowing how to port your Swift code to the latest version·Learn how to write programs that work on most of the major platforms such as iOS and LinuxWho This Book Is ForThe book is for those who are familiar with Swift but are in need of clear guidance on what's changed in the latest version and the new features.What You Will Learn·Migrate a Swift 2.2 project to Swift 3·Understand the workings of Swift Package Manager·Interact with Cocoa libraries when importing Objective C to Swift·Explore the function and operator changes new in Swift 3·Work with the advanced type changes, attribute improvements, and floating point type improvements in Swift·Discover the changes in the Swift API and see how Objective-C can be manipulated in the current API·Implement the new features central to Swift Testing and understand the new debug features·Create server-side applications using Swift 3In DetailSince Swift was introduced by Apple in WWDC 2015, it has gone on to become one of the most beloved languages to develop iOS applications with. In the new version, the Swift team aimed to take its adoption to the next level by making it available for new platforms and audiences.This book will very quickly get you up to speed and productive with Swift 3. You will begin by understanding the process of submitting new feature requests for future versions of Swift. Swift 3 allows you to develop and run your applications on a Linux machine. Using this feature, you will write your first Linux application using the debugger in Linux. Using Swift migrator, you will initiate a conversion from Swift 2.2 to Swift 3.Further on, you will learn how to interact with Cocoa libraries when importing Objective C to Swift. You will explore the function and operator changes new to Swift 3, followed by Collection and Closure changes. You will also see the changes in Swift 3 that allow you write tests easier with XCTest and debug your running code better with new formats as well. Finally, you will have a running server written completely in Swift on a Linux box.By the end of the book, you will know everything you need to know to dive into Swift 3 and build successful projects.Style and approachThe book takes a tutorial-based approach offering an overview of the new features introduced in the latest version of Swift. It includes relevant examples of how code and concepts change when it comes to working on Swift 3 compared to previous versions.

A hands on approach to learning ReasonML from the perspective of a web developer. Key Features * Hands on learning by building a real world app shell that includes client-side routing and more. * Understand Reason’s ecosystem including BuckleScript and various npm workflows. * Learn how Reason differs from TypeScript and Flow, and how to use it to make refactoring less stressful. Book Description ReasonML, also known as Reason, is a new syntax and toolchain for OCaml that was created by Facebook and is meant to be approachable for web developers. Although OCaml has several resources, most of them are from the perspective of systems development. This book, alternatively, explores Reason from the perspective of web development. You'll learn how to use Reason to build safer, simpler React applications and why you would want to do so. Reason supports immutability by default, which works quite well in the context of React. In learning Reason, you will also learn about its ecosystem – BuckleScript, JavaScript interoperability, and various npm workflows. We learn by building a real-world app shell, including a client-side router with page transitions, that we can customize for any Reason project. You'll learn how to leverage OCaml's excellent type system to enforce guarantees about business logic, as well as preventing runtime type errors.You'll also see how the type system can help offload concerns that we once had to keep in our heads. We'll explore using CSS-in-Reason, how to use external JSON in Reason, and how to unit-test critical business logic. By the end of the book, you'll understand why Reason is exploding in popularity and will have a solid foundation on which to continue your journey with Reason. What you will learn * Learn why Reason is exploding in popularity and why it's the future of React * Become familiar with Reason's syntax and semantics * Learn about Reason's ecosystem: BuckleScript and JavaScript interoperability * Learn how to build React applications with Reason * Learn how to use Reason's type system as a tool to provide amazing guarantees * Gain a solid foundation on which to continue your journey Who this book is for The target audience of this book is web developers who are somewhat familiar with ReactJS and who want to learn why ReasonML is the future of ReactJS.

Test, fuzz, and break web applications and services using Burp Suite’s powerful capabilities Key Features * Master the skills to perform various types of security tests on your web applications * Get hands-on experience working with components like scanner, proxy, intruder and much more * Discover the best-way to penetrate and test web applications Book Description Burp suite is a set of graphic tools focused towards penetration testing of web applications. Burp suite is widely used for web penetration testing by many security professionals for performing different web-level security tasks. The book starts by setting up the environment to begin an application penetration test. You will be able to configure the client and apply target whitelisting. You will also learn to setup and configure Android and IOS devices to work with Burp Suite. The book will explain how various features of Burp Suite can be used to detect various vulnerabilities as part of an application penetration test. Once detection is completed and the vulnerability is confirmed, you will be able to exploit a detected vulnerability using Burp Suite. The book will also covers advanced concepts like writing extensions and macros for Burp suite. Finally, you will discover various steps that are taken to identify the target, discover weaknesses in the authentication mechanism, and finally break the authentication implementation to gain access to the administrative console of the application. By the end of this book, you will be able to effectively perform end-to-end penetration testing with Burp Suite. What you will learn * Set up Burp Suite and its configurations for an application penetration test * Proxy application traffic from browsers and mobile devices to the server * Discover and identify application security issues in various scenarios * Exploit discovered vulnerabilities to execute commands * Exploit discovered vulnerabilities to gain access to data in various datastores * Write your own Burp Suite plugin and explore the Infiltrator module * Write macros to automate tasks in Burp Suite Who this book is for If you are interested in learning how to test web applications and the web part of mobile applications using Burp, then this is the book for you. It is specifically designed to meet your needs if you have basic experience in using Burp and are now aiming to become a professional Burp user.

Learn quick and effective techniques for developing blockchain-based distributed ledgers with ease Key Features * Discover why blockchain is a game changer in the technology landscape * Set up blockchain networks using Hyperledger Fabric * Write smart contracts at speed with Hyperledger Composer Book Description Blockchain and Hyperledger are open source technologies that power the development of decentralized applications. This Learning Path is your helpful reference for exploring and building blockchain networks using Ethereum, Hyperledger Fabric, and Hyperledger Composer. Blockchain Development with Hyperledger will start off by giving you an overview of blockchain and demonstrating how you can set up an Ethereum development environment for developing, packaging, building, and testing campaign-decentralized applications. You'll then explore the de facto language Solidity, which you can use to develop decentralized applications in Ethereum. Following this, you'll be able to configure Hyperledger Fabric and use it to build private blockchain networks and applications that connect to them. Toward the later chapters, you'll learn how to design and launch a network, and even implement smart contracts in chain code. By the end of this Learning Path, you'll be able to build and deploy your own decentralized applications by addressing the key pain points encountered in the blockchain life cycle. This Learning Path includes content from the following Packt products: * Blockchain Quick Start Guide by Xun (Brian) Wu and Weimin Sun * Hands-On Blockchain with Hyperledger by Nitin Gaur et al. What you will learn * Understand why decentralized applications are necessary * Develop and test a decentralized application with Hyperledger Fabric and Hyperledger Composer * Write and test a smart contract using Solidity * Design transaction models and chain code with Golang * Deploy the Composer REpresentational State Transfer (REST) Gateway to access Composer transactions * Maintain, monitor, and manage your blockchain solutions Who this book is for This Learning Path is designed for blockchain developers who want to build decentralized applications and smart contracts from scratch using Hyperledger. Basic familiarity with or exposure to any programming language will be useful to get started with this course.

Go beyond the basics and unleash the full power of QGIS 3.4 and 3.6 with practical, step-by-step examples Key Features * One-stop solution to all of your GIS needs * Master QGIS by learning about database integration, and geoprocessing tools * Learn about the new and updated Processing toolbox and perform spatial analysis Book Description QGIS is an open source solution to GIS and widely used by GIS professionals all over the world. It is the leading alternative to proprietary GIS software. Although QGIS is described as intuitive, it is also, by default, complex. Knowing which tools to use and how to apply them is essential to producing valuable deliverables on time. Starting with a refresher on the QGIS basics and getting you acquainted with the latest QGIS 3.6 updates, this book will take you all the way through to teaching you how to create a spatial database and a GeoPackage. Next, you will learn how to style raster and vector data by choosing and managing different colors. The book will then focus on processing raster and vector data. You will be then taught advanced applications, such as creating and editing vector data. Along with that, you will also learn about the newly updated Processing Toolbox, which will help you develop the advanced data visualizations. The book will then explain to you the graphic modeler, how to create QGIS plugins with PyQGIS, and how to integrate Python analysis scripts with QGIS. By the end of the book, you will understand how to work with all aspects of QGIS and will be ready to use it for any type of GIS work. What you will learn * Create and manage a spatial database * Get to know advanced techniques to style GIS data * Prepare both vector and raster data for processing * Add heat maps, live layer effects, and labels to your maps * Master LAStools and GRASS integration with the Processing Toolbox * Edit and repair topological data errors * Automate workflows with batch processing and the QGIS Graphical Modeler * Integrate Python scripting into your data processing workflows * Develop your own QGIS plugins Who this book is for If you are a GIS professional, a consultant, a student, or perhaps a fast learner who wants to go beyond the basics of QGIS, then this book is for you. It will prepare you to realize the full potential of QGIS.

Gain basic skills in network forensics and learn how to apply them effectively Key Features * Investigate network threats with ease * Practice forensics tasks such as intrusion detection, network analysis, and scanning * Learn forensics investigation at the network level Book Description Network forensics is a subset of digital forensics that deals with network attacks and their investigation. In the era of network attacks and malware threat, it’s now more important than ever to have skills to investigate network attacks and vulnerabilities. Hands-On Network Forensics starts with the core concepts within network forensics, including coding, networking, forensics tools, and methodologies for forensic investigations. You’ll then explore the tools used for network forensics, followed by understanding how to apply those tools to a PCAP file and write the accompanying report. In addition to this, you will understand how statistical flow analysis, network enumeration, tunneling and encryption, and malware detection can be used to investigate your network. Towards the end of this book, you will discover how network correlation works and how to bring all the information from different types of network devices together. By the end of this book, you will have gained hands-on experience of performing forensics analysis tasks. What you will learn * Discover and interpret encrypted traffic * Learn about various protocols * Understand the malware language over wire * Gain insights into the most widely used malware * Correlate data collected from attacks * Develop tools and custom scripts for network forensics automation Who this book is for The book targets incident responders, network engineers, analysts, forensic engineers and network administrators who want to extend their knowledge from the surface to the deep levels of understanding the science behind network protocols, critical indicators in an incident and conducting a forensic search over the wire.

This CRM masterclass gives you a proven approach to modern customer relationship management Key Features * Proven techniques to architect CRM systems that perform well, that are built on time and on budget, and that deliver value for many years * Combines technical knowledge and business experience to provide a powerful guide to CRM implementation * Covers modern CRM opportunities and challenges including machine learning, cloud hosting, and GDPR compliance Book Description CRM systems have delivered huge value to organizations. This book shares proven and cutting-edge techniques to increase the power of CRM even further. In The Art of CRM, Max Fatouretchi shares his decades of experience building successful CRM systems that make a real difference to business performance. Through clear processes, actionable advice, and informative case studies, The Art of CRM teaches you to design successful CRM systems for your clients. Fatouretchi, founder of Academy4CRM institute, draws on his experience over 20 years and 200 CRM implementations worldwide. Bringing CRM bang up to date, The Art of CRM shows how to add AI and machine learning, ensure compliance with GDPR, and choose between on-premise, cloud, and hybrid hosting solutions. If you’re looking for an expert guide to real-world CRM implementations, this book is for you. What you will learn * Deliver CRM systems that are on time, on budget, and bring lasting value to organizations * Build CRM that excels at operations, analytics, and collaboration * Gather requirements effectively: identify key pain points, objectives, and functional requirements * Develop customer insight through 360-degree client view and client profiling * Turn customer requirements into a CRM design spec * Architect your CRM platform * Bring machine learning and artificial intelligence into your CRM system * Ensure compliance with GDPR and other critical regulations * Choose between on-premise, cloud, and hybrid hosting solutions Who this book is for CRM practitioners who want to update their work with new, proven techniques and approaches

A collection of in-depth conversations with leading developer advocates that reveal the world of developer relations today Key Features * Top developer advocates reveal the work they’re doing at the center of their tech communities and the impact their advocacy is having on the tech industry as a whole * Discover the best practices of developer advocacy and get the inside story on working at some of the world’s largest tech companies * Features contributions from noted developer advocates, including Scott Hanselman, Sally Eaves, Venkat Subramaniam, Jono Bacon, Ted Neward, and more Book Description What exactly is a developer advocate, and how do they connect developers and companies around the world? Why is the area of developer relations set to explode? Can anybody with a passion for tech become a developer advocate? What are the keys to success on a global scale? How does a developer advocate maintain authenticity when balancing the needs of their company and their tech community? What are the hot topics in areas including Java, JavaScript, "tech for good," artificial intelligence, blockchain, the cloud, and open source? These are just a few of the questions addressed by developer advocate and author Geertjan Wielenga in Developer, Advocate!. 32 of the industry's most prominent developer advocates, from companies including Oracle, Microsoft, Google, and Amazon, open up about what it's like to turn a lifelong passion for knowledge sharing about tech into a rewarding career. These advocates run the gamut from working at large software vendors to small start-ups, along with independent developer advocates who work within organizations or for themselves. In Developer, Advocate!, readers will see how developer advocates are actively changing the world, not only for developers, but for individuals and companies navigating the fast-changing tech landscape. More importantly, Developer, Advocate! serves as a rallying cry to inspire and motivate tech enthusiasts and burgeoning developer advocates to get started and take their first steps within their tech community. What you will learn * Discover how developer advocates are putting developer interests at the heart of the software industry in companies including Microsoft and Google * Gain the confidence to use your voice in the tech community * Immerse yourself in developer advocacy techniques * Understand and overcome the challenges and obstacles facing developer advocates today * Hear predictions from the people at the cutting edge of tech * Explore your career options in developer advocacy Who this book is for Anybody interested in developer advocacy, the impact it is having, and how to build developer advocacy capabilities

A comprehensive guide to get started with Java and gain insights into major concepts such as object-oriented, functional, and reactive programming Key Features * Strengthen your knowledge of important programming concepts and the latest features in Java * Explore core programming topics including GUI programming, concurrency, and error handling * Learn the idioms and best practices for writing high-quality Java code Book Description Java is one of the preferred languages among developers, used in everything right from smartphones, and game consoles to even supercomputers, and its new features simply add to the richness of the language. This book on Java programming begins by helping you learn how to install the Java Development Kit. You will then focus on understanding object-oriented programming (OOP), with exclusive insights into concepts like abstraction, encapsulation, inheritance, and polymorphism, which will help you when programming for real-world apps. Next, you’ll cover fundamental programming structures of Java such as data structures and algorithms that will serve as the building blocks for your apps. You will also delve into core programming topics that will assist you with error handling, debugging, and testing your apps. As you progress, you’ll move on to advanced topics such as Java libraries, database management, and network programming, which will hone your skills in building professional-grade apps. Further on, you’ll understand how to create a graphic user interface using JavaFX and learn to build scalable apps by taking advantage of reactive and functional programming. By the end of this book, you’ll not only be well versed with Java 10, 11, and 12, but also gain a perspective into the future of this language and software development in general. What you will learn * Learn and apply object-oriented principles * Gain insights into data structures and understand how they are used in Java * Explore multithreaded, asynchronous, functional, and reactive programming * Add a user-friendly graphic interface to your application * Find out what streams are and how they can help in data processing * Discover the importance of microservices and use them to make your apps robust and scalable * Explore Java design patterns and best practices to solve everyday problems * Learn techniques and idioms for writing high-quality Java code Who this book is for Students, software developers, or anyone looking to learn new skills or even a language will find this book useful. Although this book is for beginners, professional programmers can benefit from it too. Previous knowledge of Java or any programming language is not required.

Supervised and unsupervised machine learning made easy in Scala with this quick-start guide. Key Features * Construct and deploy machine learning systems that learn from your data and give accurate predictions * Unleash the power of Spark ML along with popular machine learning algorithms to solve complex tasks in Scala. * Solve hands-on problems by combining popular neural network architectures such as LSTM and CNN using Scala with DeepLearning4j library Book Description Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to develop and train effective machine learning models in Scala. The book starts with an introduction to machine learning, while covering deep learning and machine learning basics. It then explains how to use Scala-based ML libraries to solve classification and regression problems using linear regression, generalized linear regression, logistic regression, support vector machine, and Na?ve Bayes algorithms. It also covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning techniques, such as dimensionality reduction, clustering, and recommender systems. Finally, it provides a brief overview of deep learning using a real-life example in Scala. What you will learn * Get acquainted with JVM-based machine learning libraries for Scala such as Spark ML and Deeplearning4j * Learn RDDs, DataFrame, and Spark SQL for analyzing structured and unstructured data * Understand supervised and unsupervised learning techniques with best practices and pitfalls * Learn classification and regression analysis with linear regression, logistic regression, Na?ve Bayes, support vector machine, and tree-based ensemble techniques * Learn effective ways of clustering analysis with dimensionality reduction techniques * Learn recommender systems with collaborative filtering approach * Delve into deep learning and neural network architectures Who this book is for This book is for machine learning developers looking to train machine learning models in Scala without spending too much time and effort. Some fundamental knowledge of Scala programming and some basics of statistics and linear algebra is all you need to get started with this book.

Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications Key Features * Explore advanced financial models used by the industry and ways of solving them using Python * Build state-of-the-art infrastructure for modeling, visualization, trading, and more * Empower your financial applications by applying machine learning and deep learning Book Description The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples. You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance. By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis. What you will learn * Solve linear and nonlinear models representing various financial problems * Perform principal component analysis on the DOW index and its components * Analyze, predict, and forecast stationary and non-stationary time series processes * Create an event-driven backtesting tool and measure your strategies * Build a high-frequency algorithmic trading platform with Python * Replicate the CBOT VIX index with SPX options for studying VIX-based strategies * Perform regression-based and classification-based machine learning tasks for prediction * Use TensorFlow and Keras in deep learning neural network architecture Who this book is for If you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.

A complete guide to understanding, developing, and testing popular security-token smart contracts Key Features * Understand key Blockchain and Ethereum platforms concepts * Step-by-step guide to developing STO smart contracts on Ethereum * Monetize digital tokens under various U.S. securities laws Book Description The failure of initial coin offerings (ICOs) is no accident, as most ICOs do not link to a real asset and are not regulated. Realizing the shortcomings of ICOs, the blockchain community and potential investors embraced security token offerings (STOs) and stablecoins enthusiastically. In this book, we start with an overview of the blockchain technology along with its basic concepts. We introduce the concept behind STO, and cover the basic requirements for launching a STO and the relevant regulations governing its issuance. We discuss U.S. securities laws development in launching security digital tokens using blockchain technology and show some real use cases. We also explore the process of STO launches and legal considerations. We introduce popular security tokens in the current blockchain space and talk about how to develop a security token DApp, including smart contract development for ERC1404 tokens. Later, you'll learn to build frontend side functionalities to interact with smart contracts. Finally, we discuss stablecoin technical design functionalities for issuing and operating STO tokens by interacting with Ethereum smart contracts. By the end of this book, you will have learned more about STOs and gained a detailed knowledge of building relevant applications—all with the help of practical examples. What you will learn * Understand the basic requirements for launching a security token offering * Explore various US securities laws governing the offering of security digital tokens * Get to grips with the stablecoin concept with the help of use cases * Learn how to develop security token decentralized applications * Understand the difference between ERC-20 and ERC-721 tokens * Learn how to set up a development environment and build security tokens * Explore the technical design of stablecoins Who this book is for This book is ideal for blockchain beginners and business user developers who want to quickly master popular Security Token Offerings and stablecoins. Readers will learn how to develop blockchain/digital cryptos, guided by U.S. securities laws and utilizing some real use cases. Prior exposure to an Object-Oriented Programming language such as JavaScript would be an advantage, but is not mandatory.

Teach your machine to think for itself! Key Features * Delve into supervised learning and grasp how a machine learns from data * Implement popular machine learning algorithms from scratch, developing a deep understanding along the way * Explore some of the most popular scientific and mathematical libraries in the Python language Book Description Supervised machine learning is used in a wide range of sectors (such as finance, online advertising, and analytics) because it allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more while the system self-adjusts and makes decisions on its own. As a result, it's crucial to know how a machine “learns” under the hood. This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You’ll embark on this journey with a quick overview and see how supervised machine learning differs from unsupervised learning. Next, we explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning. By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and powerfully apply algorithms to new problems. What you will learn * Crack how a machine learns a concept and generalize its understanding to new data * Uncover the fundamental differences between parametric and non-parametric models * Implement and grok several well-known supervised learning algorithms from scratch * Work with models in domains such as ecommerce and marketing * Expand your expertise and use various algorithms such as regression, decision trees, and clustering * Build your own models capable of making predictions * Delve into the most popular approaches in deep learning such as transfer learning and neural networks Who this book is for This book is for aspiring machine learning developers who want to get started with supervised learning. Intermediate knowledge of Python programming—and some fundamental knowledge of supervised learning—are expected.