Hands-On Design Patterns with Delphi. Build applications using idiomatic, extensible, and concurrent design patterns in Delphi

Primož Gabrijelčič

Design patterns have proven to be the go-to solution for many common programming scenarios. This book focuses on design patterns applied to the Delphi language. The book will provide you with insights into the language and its capabilities of a runtime library.You'll start by exploring a variety of design patterns and understanding them through real-world examples. This will entail a short explanation of the concept of design patterns and the original set of the 'Gang of Four' patterns, which will help you in structuring your designs efficiently. Next, you'll cover the most important 'anti-patterns' (essentially bad software development practices) to aid you in steering clear of problems during programming. You'll then learn about the eight most important patterns for each creational, structural, and behavioral type. After this, you'll be introduced to the concept of 'concurrency' patterns, which are design patterns specifically related to multithreading and parallel computation. These will enable you to develop and improve an interface between items and harmonize shared memories within threads. Toward the concluding chapters, you'll explore design patterns specific to program design and other categories of patterns that do not fall under the 'design' umbrella.By the end of this book, you'll be able to address common design problems encountered while developing applications and feel confident while building scalable projects.

Hands-On Machine Learning on Google Cloud Platform. Implementing smart and efficient analytics using Cloud ML Engine

Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier

Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions.This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications.By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems.

D3.js 4.x Data Visualization. Learn to visualize your data with JavaScript - Third Edition

Aendrew Rininsland, Swizec Teller

Want to get started with impressive interactive visualizations and implement them in your daily tasks? This book offers the perfect solution-D3.js. It has emerged as the most popular tool for data visualization. This book will teach you how to implement the features of the latest version of D3 while writing JavaScript using the newest tools and techniqueYou will start by setting up the D3 environment and making your first basic bar chart. You will then build stunning SVG and Canvas-based data visualizations while writing testable, extensible code,as accurate and informative as it is visually stimulating. Step-by-step examples walk you through creating, integrating, and debugging different types of visualization and will have you building basic visualizations (such as bar, line, and scatter graphs) in no time.By the end of this book, you will have mastered the techniques necessary to successfully visualize data and will be ready to use D3 to transform any data into an engaging and sophisticated visualization.

Hands-On Unsupervised Learning with Python. Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more

Giuseppe Bonaccorso

Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python.This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images.By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges.

Rust High Performance. Learn to skyrocket the performance of your Rust applications

Iban Eguia Moraza

This book teaches you how to optimize the performance of your Rust code so that it is at the same level as languages such as C/C++. You'll understand and fi x common pitfalls, learn how to improve your productivity by using metaprogramming, and speed up your code. You will master the features of the language, which will make you stand out, and use them to greatly improve the efficiency of your algorithms. The book begins with an introduction to help you identify bottlenecks when programming in Rust. We highlight common performance pitfalls, along with strategies to detect and resolve these issues early. We move on to mastering Rust's type system, which will enable us to optimize both performance and safety at compile time. You will learn how to effectively manage memory in Rust, mastering the borrow checker. We move on to measuring performance and you will see how this affects the way you write code. Moving forward, you will perform metaprogramming in Rust to boost the performance of your code and your productivity. Finally, you will learn parallel programming in Rust, which enables efficient and faster execution by using multithreading and asynchronous programming.

Learning Robotic Process Automation. Create Software robots and automate business processes with the leading RPA tool – UiPath

Alok Mani Tripathi

Robotic Process Automation (RPA) enables automating business processes using software robots. Software robots interpret, trigger responses, and communicate with other systems just like humans do. Robotic processes and intelligent automation tools can help businesses improve the effectiveness of services faster and at a lower cost than current methods.This book is the perfect start to your automation journey, with a special focus on one of the most popular RPA tools: UiPath.Learning Robotic Process Automation takes you on a journey from understanding the basics of RPA to advanced implementation techniques. You will become familiar with the UiPath interface and learn about its workflow. Once you are familiar with the environment, we will get hands-on with automating applications such as Excel, SAP, Windows and web applications, screen and web scraping, working with user events, and we'll cover exceptions and debugging. By the end of the book, you'll not only be able to build your first software robot, but you'll also wire it up to perform various automation tasks with the help of best practices for robot deployment.

Neural Networks with Keras Cookbook. Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots

V Kishore Ayyadevara

This book will take you from the basics of neural networks to advanced implementations of architectures using a recipe-based approach.We will learn about how neural networks work and the impact of various hyper parameters on a network's accuracy along with leveraging neural networks for structured and unstructured data.Later, we will learn how to classify and detect objects in images. We will also learn to use transfer learning for multiple applications, including a self-driving car using Convolutional Neural Networks.We will generate images while leveraging GANs and also by performing image encoding. Additionally, we will perform text analysis using word vector based techniques. Later, we will use Recurrent Neural Networks and LSTM to implement chatbot and Machine Translation systems.Finally, you will learn about transcribing images, audio, and generating captions and also use Deep Q-learning to build an agent that plays Space Invaders game.By the end of this book, you will have developed the skills to choose and customize multiple neural network architectures for various deep learning problems you might encounter.

Cloud Native Python. Build and deploy resilent applications on the cloud using microservices, AWS, Azure and more

Manish Sethi

Businesses today are evolving so rapidly that having their own infrastructure to support their expansion is not feasible. As a result, they have been resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This book will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you’ll learn how to build microservices in Python using REST APIs in an event driven approach and you will build the web layer. Next, you’ll learn about Interacting data services and building Web views with React, after which we will take a detailed look at application security and performance. Then, you’ll also learn how to Dockerize your services. And finally, you’ll learn how to deploy the application on the AWS and Azure platforms. We will end the book by discussing some concepts and techniques around troubleshooting problems that might occur with your applications after you’ve deployed them. This book will teach you how to craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: we're going to build everything using Python 3 and its amazing tooling ecosystem. The book will take you on a journey, the destination of which, is the creation of a complete Python application based on microservices over the cloud platform

Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems

Matthew Lamons, Rahul Kumar, Abhishek Nagaraja

Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier.Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You’ll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system.Similarly, you’ll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you’ll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects.By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way

Implementing Cisco UCS Solutions. Deploy, manage, and automate your datacenter - Second Edition

Anuj Modi, Prasenjit Sarkar

Cisco Unified Computer System (UCS) is a powerful solution for modern data centers and is responsible for increasing efficiency and reducing costs. This hands-on guide will take you through deployment in Cisco UCS. Using real-world examples of configuring and deploying Cisco UCS components, we’ll prepare you for the practical deployments of Cisco UCS data center solutions. If you want to develop and enhance your hands-on skills with Cisco UCS solutions, this book is certainly for you.We start by showing you the Cisco UCS equipment options then introduce Cisco UCS Emulator so you can learn and practice deploying Cisco UCS components. We’ll also introduce you to all the areas of UCS solutions through practical configuration examples.Moving on, you’ll explore the Cisco UCS Manager, which is the centralized management interface for Cisco UCS. Once you get to know UCS Manager, you’ll dive deeper into configuring LAN, SAN, identity pools, resource pools, and service profiles for the servers. You’ll also get hands-on with administration topics including backup, restore, user’s roles, and high availability cluster configuration. Finally, you will learn about virtualized networking, third-party integration tools, and testing failure scenarios.By the end of this book, you’ll know everything you need to know to rapidly grow Cisco UCS deployments in the real world.

Mastering Arduino. A project-based approach to electronics, circuits, and programming

Jon Hoffman

Mastering Arduino is an all-in-one guide to getting the most out of your Arduino. This practical, no-nonsense guide teaches you all of the electronics and programming skills that you need to create advanced Arduino projects. This book is packed full of real-world projects for you to practice on, bringing all of the knowledge in the book together and giving you the skills to build your own robot from the examples in this book. The final two chapters discuss wireless technologies and how they can be used in your projects. The book begins with the basics of electronics, making sure that you understand components, circuits, and prototyping before moving on. It then performs the same function for code, getting you into the Arduino IDE and showing you how to connect the Arduino to a computer and run simple projects on your Arduino.Once the basics are out of the way, the next 10 chapters of the book focus on small projects centered around particular components, such as LCD displays, stepper motors, or voice synthesizers. Each of these chapters will get you familiar with the technology involved, how to build with it, how to program it, and how it can be used in your own projects.

Practical Security Automation and Testing. Tools and techniques for automated security scanning and testing in DevSecOps

Tony Hsiang-Chih Hsu

Security automation is the automatic handling of software security assessments tasks. This book helps you to build your security automation framework to scan for vulnerabilities without human intervention.This book will teach you to adopt security automation techniques to continuously improve your entire software development and security testing. You will learn to use open source tools and techniques to integrate security testing tools directly into your CI/CD framework. With this book, you will see how to implement security inspection at every layer, such as secure code inspection, fuzz testing, Rest API, privacy, infrastructure security, and web UI testing. With the help of practical examples, this book will teach you to implement the combination of automation and Security in DevOps. You will learn about the integration of security testing results for an overall security status for projects.By the end of this book, you will be confident implementing automation security in all layers of your software development stages and will be able to build your own in-house security automation platform throughout your mobile and cloud releases.

Java 9 High Performance. Practical techniques and best practices for optimizing Java applications through concurrency, reactive programming, and more

Mayur Ramgir, Nick Samoylov

Finally, a book that focuses on the practicalities rather than theory of Java application performance tuning. This book will be your one-stop guide to optimize the performance of your Java applications.We will begin by understanding the new features and APIs of Java 9. You will then be taught the practicalities of Java application performance tuning, how to make the best use of garbage collector, and find out how to optimize code with microbenchmarking. Moving ahead, you will be introduced to multithreading and learning about concurrent programming with Java 9 to build highly concurrent and efficient applications. You will learn how to fine tune your Java code for best results. You will discover techniques on how to benchmark performance and reduce various bottlenecks in your applications. We'll also cover best practices of Java programming that will help you improve the quality of your codebase.By the end of the book, you will be armed with the knowledge to build and deploy efficient, scalable, and concurrent applications in Java.

Learning Malware Analysis. Explore the concepts, tools, and techniques to analyze and investigate Windows malware

Monnappa K A

Malware analysis and memory forensics are powerful analysis and investigation techniques used in reverse engineering, digital forensics, and incident response. With adversaries becoming sophisticated and carrying out advanced malware attacks on critical infrastructures, data centers, and private and public organizations, detecting, responding to, and investigating such intrusions is critical to information security professionals. Malware analysis and memory forensics have become must-have skills to fight advanced malware, targeted attacks, and security breaches.This book teaches you the concepts, techniques, and tools to understand the behavior and characteristics of malware through malware analysis. It also teaches you techniques to investigate and hunt malware using memory forensics. This book introduces you to the basics of malware analysis, and then gradually progresses into the more advanced concepts of code analysis and memory forensics. It uses real-world malware samples, infected memory images, and visual diagrams to help you gain a better understanding of the subject and to equip you with the skills required to analyze, investigate, and respond to malware-related incidents.

Machine Learning with scikit-learn Quick Start Guide. Classification, regression, and clustering techniques in Python

Kevin Jolly

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize, and evaluate all of the important machine learning algorithms that scikit-learn provides.This book teaches you how to use scikit-learn for machine learning. You will start by setting up and configuring your machine learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine learning models. You will learn classification, regression, and clustering techniques to work with different types of datasets and train your models.Finally, you will learn about an effective pipeline to help you build a machine learning project from scratch. By the end of this book, you will be confident in building your own machine learning models for accurate predictions.

Practical Predictive Analytics. Analyse current and historical data to predict future trends using R, Spark, and more

Ralph Winters

This is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get startedwith a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio,and a description of the best practices for organizing your projects.On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement andsuccessfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn whycollaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model.We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data.