Let Python do the heavy lifting for you as you analyze large datasets.

Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner’s guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights. This new edition is updated for the latest version of Python and includes current, relevant data examples.

• Get a firm background in the basics of Python coding for data analysis
• Learn about data science careers you can pursue with Python coding skills
• Integrate data analysis with multimedia and graphics
• Manage and organize data with cloud-based relational databases

Python careers are on the rise. Grab this user-friendly Dummies guide and gain the programming skills you need to become a data pro.

Wenn Sie Webseiten oder mobile Apps entwickeln möchten, dann ist dieses Buch wie für Sie gemacht! Auch ganz ohne Vorkenntnisse steigen Sie einfach ein und lernen die einzelnen Programmiersprachen und Technologien jeweils für sich und im Zusammenspiel kennen und einsetzen. Angefangen beim grundlegenden Aufbau einer Webseite mit HTML, CSS und JavaScript über die Entwicklung mobiler Apps für iOS- und Android-Geräte mit Flutter bis hin zur Verarbeitung der Daten mit Python: Hier ist einfach mehr für Sie drin! Wenn Sie sich einen breiten Überblick über die Webentwicklung und Programmierung verschaffen wollen, dann werfen Sie am besten gleich einen Blick in dieses Buch ...

As a web developer, you may not want to spend time making your web app secure, but it definitely comes with the territory. This practical guide provides you with the latest information on how to thwart security threats at several levels, including new areas such as microservices. You'll learn how to help protect your app no matter where it runs, from the latest smartphone to an older desktop, and everything in between. Author John Paul Mueller delivers specific advice as well as several security programming examples for developers with a good knowledge of CSS3, HTML5, and JavaScript. In five separate sections, this book shows you how to protect against viruses, DDoS attacks, security breaches, and other nasty intrusions. Create a security plan for your organization that takes the latest devices and user needs into account Develop secure interfaces, and safely incorporate third-party code from libraries, APIs, and microservices Use sandboxing techniques, in-house and third-party testing techniques, and learn to think like a hacker Implement a maintenance cycle by determining when and how to update your application software Learn techniques for efficiently tracking security threats as well as training requirements that your organization can use

Thwart hackers by preventing, detecting, and misdirecting access before they can plant malware, obtain credentials, engage in fraud, modify data, poison models, corrupt users, eavesdrop, and otherwise ruin your day Key Features Discover how hackers rely on misdirection and deep fakes to fool even the best security systems Retain the usefulness of your data by detecting unwanted and invalid modifications Develop application code to meet the security requirements related to machine learning Book DescriptionBusinesses are leveraging the power of AI to make undertakings that used to be complicated and pricy much easier, faster, and cheaper. The first part of this book will explore these processes in more depth, which will help you in understanding the role security plays in machine learning. As you progress to the second part, you'll learn more about the environments where ML is commonly used and dive into the security threats that plague them using code, graphics, and real-world references. The next part of the book will guide you through the process of detecting hacker behaviors in the modern computing environment, where fraud takes many forms in ML, from gaining sales through fake reviews to destroying an adversary's reputation. Once you've understood hacker goals and detection techniques, you'll learn about the ramifications of deep fakes, followed by mitigation strategies. This book also takes you through best practices for embracing ethical data sourcing, which reduces the security risk associated with data. You'll see how the simple act of removing personally identifiable information (PII) from a dataset lowers the risk of social engineering attacks. By the end of this machine learning book, you'll have an increased awareness of the various attacks and the techniques to secure your ML systems effectively. What you will learn Explore methods to detect and prevent illegal access to your system Implement detection techniques when access does occur Employ machine learning techniques to determine motivations Mitigate hacker access once security is breached Perform statistical measurement and behavior analysis Repair damage to your data and applications Use ethical data collection methods to reduce security risks Who this book is forWhether you're a data scientist, researcher, or manager working with machine learning techniques in any aspect, this security book is a must-have. While most resources available on this topic are written in a language more suitable for experts, this guide presents security in an easy-to-understand way, employing a host of diagrams to explain concepts to visual learners. While familiarity with machine learning concepts is assumed, knowledge of Python and programming in general will be useful.

Thorough coverage of Microsoft's new dynamic programming language: IronPython

IronPython is a powerful and vital part of any .NET developer's toolbox, and although it is several years old, very little literature exists on the topic. This essential resource fills that void and provides you with an in-depth understanding of IronPython.

A brief introduction walks you through the installation, usage, and tools of IronPython and also explains what makes IronPython different from other programming languages. Coverage quickly moves on to explaining how to use and work with the IronPython language, and an in-depth look at its environment sheds light on how it can be stand alone or with the .NET Framework. You'll see how IronPython can be used to create either desktop or Web-based applications and you'll witness how it interacts with other existing technologies. In addition, coverage of advanced topics shares techniques for extending IronPython and making it a robust language.Provides you with an in-depth look at IronPython, how it is different from other programming languages, what it is capable of, and how to maximize its potentialExplores how IronPython interacts with existing technologies and how it can perform administration tasksAnswers popular questions, such as how to extend IronPython and make it a more robust languageTackles topics not addressed anywhere else, including executing IronPython using Mono

You'll want to devour every topic covered in "Professional IronPython" so you can get started working with this powerful programming language today.