Mastering Blockchain Programming with Solidity. Write production-ready smart contracts for Ethereum blockchain with Solidity

Jitendra Chittoda

Solidity is among the most popular and contract-oriented programming languages used for writing decentralized applications (DApps) on Ethereum blockchain. If you’re looking to perfect your skills in writing professional-grade smart contracts using Solidity, this book can help.You will get started with a detailed introduction to blockchain, smart contracts, and Ethereum, while also gaining useful insights into the Solidity programming language. A dedicated section will then take you through the different Ethereum Request for Comments (ERC) standards, including ERC-20, ERC-223, and ERC-721, and demonstrate how you can choose among these standards while writing smart contracts. As you approach later chapters, you will cover the different smart contracts available for use in libraries such as OpenZeppelin. You’ll also learn to use different open source tools to test, review and improve the quality of your code and make it production-ready. Toward the end of this book, you’ll get to grips with techniques such as adding security to smart contracts, and gain insights into various security considerations. By the end of this book, you will have the skills you need to write secure, production-ready smart contracts in Solidity from scratch for decentralized applications on Ethereum blockchain.

Linux Mint Essentials. A practical guide to Linux Mint for the novice to the professional

Jay LaCroix

Salt Cookbook. Over 80 hands-on recipes to efficiently configure and manage your infrastructure with Salt

Anirban Saha

Combating Crime on the Dark Web. Learn how to access the dark web safely and not fall victim to cybercrime

Nearchos Nearchou

In today’s world, the crime-prevention landscape is impossible to navigate. The dark web means new frontiers of combat against bad actors that pop up daily. Everyone from narcotics dealers to human traffickers are exploiting the dark web to evade authorities. If you want to find your feet in this tricky terrain and fight crime on the dark web, take this comprehensive, easy-to-follow cyber security guide with you.Combating Crime on the Dark Web contains everything you need to be aware of when tackling the world of the dark web. Step by step, you’ll gain acumen in the tactics that cybercriminals are adopting and be equipped with the arsenal of strategies that are available to you as a cybersecurity specialist.This cyber security book ensures that you are well acquainted with all the latest techniques to combat dark web criminality. After a primer on cybercrime and the history of the dark web, you’ll dive right into the main domains of the dark web ecosystem, reaching a working understanding of how drug markets, child pornography, and human trafficking operate. Once well-versed with the functioning of criminal groups, you’ll be briefed on the most effective tools and methods being employed by law enforcement, tech companies, and others to combat such crimes, developing both a toolkit and a mindset that can help you stay safe from such criminal activities and can be applied in any sector or domain. By the end of this book, you’ll be well prepared to begin your pushback against the criminal elements of the dark web.

Mastering Transformers. Build state-of-the-art models from scratch with advanced natural language processing techniques

Savaş Yildirim, Meysam Asgari- Chenaghlu

Transformer-based language models have dominated natural language processing (NLP) studies and have now become a new paradigm. With this book, you'll learn how to build various transformer-based NLP applications using the Python Transformers library.The book gives you an introduction to Transformers by showing you how to write your first hello-world program. You'll then learn how a tokenizer works and how to train your own tokenizer. As you advance, you'll explore the architecture of autoencoding models, such as BERT, and autoregressive models, such as GPT. You'll see how to train and fine-tune models for a variety of natural language understanding (NLU) and natural language generation (NLG) problems, including text classification, token classification, and text representation. This book also helps you to learn efficient models for challenging problems, such as long-context NLP tasks with limited computational capacity. You'll also work with multilingual and cross-lingual problems, optimize models by monitoring their performance, and discover how to deconstruct these models for interpretability and explainability. Finally, you'll be able to deploy your transformer models in a production environment.By the end of this NLP book, you'll have learned how to use Transformers to solve advanced NLP problems using advanced models.

Linux Administration Best Practices. Practical solutions to approaching the design and management of Linux systems

Scott Alan Miller

Linux is a well-known, open source Unix-family operating system that is the most widely used OS today. Linux looks set for a bright future for decades to come, but system administration is rarely studied beyond learning rote tasks or following vendor guidelines. To truly excel at Linux administration, you need to understand how these systems work and learn to make strategic decisions regarding them.Linux Administration Best Practices helps you to explore best practices for efficiently administering Linux systems and servers. This Linux book covers a wide variety of topics from installation and deployment through to managing permissions, with each topic beginning with an overview of the key concepts followed by practical examples of best practices and solutions. You'll find out how to approach system administration, Linux, and IT in general, put technology into proper business context, and rethink your approach to technical decision making. Finally, the book concludes by helping you to understand best practices for troubleshooting Linux systems and servers that'll enable you to grow in your career as well as in any aspect of IT and business.By the end of this Linux administration book, you'll have gained the knowledge needed to take your Linux administration skills to the next level.

Python Real-World Projects. Craft your Python portfolio with deployable applications

Steven F. Lott

In today's competitive job market, a project portfolio often outshines a traditional resume. Python Real-World Projects empowers you to get to grips with crucial Python concepts while building complete modules and applications. With two dozen meticulously designed projects to explore, this book will help you showcase your Python mastery and refine your skills. Tailored for beginners with a foundational understanding of class definitions, module creation, and Python's inherent data structures, this book is your gateway to programming excellence. You’ll learn how to harness the potential of the standard library and key external projects like JupyterLab, Pydantic, pytest, and requests. You’ll also gain experience with enterprise-oriented methodologies, including unit and acceptance testing, and an agile development approach. Additionally, you’ll dive into the software development lifecycle, starting with a minimum viable product and seamlessly expanding it to add innovative features. By the end of this book, you’ll be armed with a myriad of practical Python projects and all set to accelerate your career as a Python programmer.

Machine Learning in Java. Helpful techniques to design, build, and deploy powerful machine learning applications in Java - Second Edition

AshishSingh Bhatia, Bostjan Kaluza

As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge.Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11.Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analysis. By the end of the book, you will have explored related web resources and technologies that will help you take your learning to the next level.By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data.