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Unlock the secrets of the finance industry and dive into the world of high-performance trading systems with C++ High Performance for Financial Systems. Trading systems are the backbone of the financial world, and understanding how to build them for optimal performance is crucial for success. If you've ever dreamt of creating scalable and cutting-edge financial software, this guide is your key to success. A cornerstone of this book is its coverage of system design and architecture. The book starts by outlining the role of C++ in finance and trading. You'll learn the principles and methodologies behind building systems that can handle vast amounts of data, execute complex trading strategies with ease, and maintain the highest levels of reliability. Armed with this knowledge, you'll be equipped to tackle even the most challenging trading scenarios.In the fast-paced world of finance, every millisecond counts. This book delves into low-latency strategies that will enable your trading systems to react with lightning speed. You’ll also learn the art of reducing latency, optimizing code, and leveraging the latest hardware and software techniques to gain a competitive edge in the market.By the end of this book, you’ll be well-versed in architecting a financial trading system as well as advanced strategies and new industry trends.
Amita Kapoor, Antonio Gulli, Sujit Pal, François Chollet
Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available.TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments.This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML.
Nitin Gaur, Anthony O'Dowd, Petr Novotny, Luc Desrosiers, ...
Blockchain with Hyperledger Fabric - Second Edition is a refreshed and extended version of the successful book on practical Hyperledger Fabric blockchain development. This edition includes many new chapters, alongside comprehensive updates and additions to the existing ones. Entirely reworked for Hyperledger Fabric version 2, this edition will bring you right up to date with the latest in blockchain. Using a real-world Trade Finance and Logistics example, with working code available on GitHub, you’ll really understand both how and why Hyperledger Fabric can be used to maximum effect. This book is your comprehensive guide and reference to explore and build blockchain networks using Hyperledger Fabric version 2.This edition of the book begins by outlining the evolution of blockchain, including an overview of relevant blockchain technologies. Starting from first principles, you’ll learn how to design and operate a permissioned blockchain network based on Hyperledger Fabric version 2. You will learn how to configure the main architectural components of a permissioned blockchain network including Peers, Orderers, Certificate Authorities, Channels, and Policies. You’ll then learn how to design, develop, package, and deploy smart contracts, and how they are subsequently used by applications. This edition also contains chapters on DevOps, blockchain governance, and security, making this your go-to book for Hyperledger Fabric version 2.
Clean Code in Python. Develop maintainable and efficient code - Second Edition
Experienced professionals in every field face several instances of disorganization, poor readability, and testability due to unstructured code.With updated code and revised content aligned to the new features of Python 3.9, this second edition of Clean Code in Python will provide you with all the tools you need to overcome these obstacles and manage your projects successfully.The book begins by describing the basic elements of writing clean code and how it plays a key role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design.The book discusses object-oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve problems by implementing software design patterns in your code. In the concluding chapter, we break down a monolithic application into a microservices-based one starting from the code as the basis for a solid platform.By the end of this clean code book, you will be proficient in applying industry-approved coding practices to design clean, sustainable, and readable real-world Python code.
Apache ActiveMQ is a powerful and popular open source messaging and Integration Patterns server. ActiveMQ is a fully JMS 1.1 compliant Message Broker and supports many advanced features beyond the JMS specification.Instant ActiveMQ Application Development How-to shows you how to get started with the ActiveMQ Message Broker. You will learn how to develop message-based applications using ActiveMQ and the JMS specification.In this book you will learn all the basic skills you need to start writing Java Messaging applications with a firm grounding in the more advanced features of ActiveMQ, giving you the tools to continue to master application development using ActiveMQ.Starting by applying the messaging features of the JMS specification to write basic messaging applications, you will develop a basic JMS application using topics and queues to broadcast events as well as perform Request and Response operations over the JMS.Once you have mastered the simple tasks you will move onto using the advanced features in ActiveMQ to supercharge your messaging applications. You will get to grips with ActiveMQ's scheduler to delay messages. You will also learn how to leverage ActiveMQ's fault-tolerant capabilities to create robust client applications.
Building on the success of its international bestselling predecessor, this third edition of the CompTIA Security+ SY0-701 Certification Guide serves as your one-stop resource for Security+ exam preparation. Written by cybersecurity expert Ian Neil, this comprehensive guide helps you unlock the intricacies of cybersecurity and understand the technology behind the CompTIA Security+ SY0-701 certification, ensuring you approach the exam with confidence and pass on your first attempt.By exploring security in detail, this book introduces essential principles, controls, and best practices. The chapters are meticulously designed to provide 100% coverage of the CompTIA Security+ SY0-701 exam objectives, ensuring you have the most up-to-date and relevant study material. By mastering cybersecurity fundamentals, you’ll acquire the knowledge and skills to identify and mitigate threats, manage vulnerabilities, and safeguard enterprise infrastructure. Additionally, the book grants lifetime access to web-based exam prep tools, including 3 full-length mock exams, flashcards, acronyms, along with a 12% Security+ exam discount voucher.Whether you aim to excel the CompTIA Security+ SY0-701 exam, advance your career in cybersecurity, or enhance your existing knowledge, this book will transform you into a cybersecurity expert.
Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining.This book will serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and libraries. You will get a hands-on demonstration of working with different real-world datasets and extracting useful insights from them using popular Python libraries such as NumPy, pandas, scikit-learn, and matplotlib. You will then learn the different stages of data mining such as data loading, cleaning, analysis, and visualization. You will also get a full conceptual description of popular data transformation, clustering, and classification techniques.By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle.