Go from total MATLAB newbie to plotting graphs and solving equations in a flash! 

MATLAB is one of the most powerful and commonly used tools in the STEM field. But did you know it doesn’t take an advanced degree or a ton of computer experience to learn it? MATLAB For Dummies is the roadmap you’ve been looking for to simplify and explain this feature-filled tool. 

This handy reference walks you through every step of the way as you learn the MATLAB language and environment inside-and-out. Starting with straightforward basics before moving on to more advanced material like Live Functions and Live Scripts, this easy-to-read guide shows you how to make your way around MATLAB with screenshots and newly updated procedures.  It includes:

• A comprehensive introduction to installing MATLAB, using its interface, and creating and saving your first file 
• Fully updated to include the 2020 and 2021 updates to MATLAB, with all-new screenshots and up-to-date procedures 
• Enhanced debugging procedures and use of the Symbolic Math Toolbox 
• Brand new instruction on working with Live Scripts and Live Functions, designing classes, creating apps, and building projects 
• Intuitive walkthroughs for MATLAB’s advanced features, including importing and exporting data and publishing your work 

Perfect for STEM students and new professionals ready to master one of the most powerful tools in the fields of engineering, mathematics, and computing, MATLAB For Dummies is the simplest way to go from complete newbie to power user faster than you would have thought possible. 

Your comprehensive entry-level guide to machine learning

While machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie Ex Machina—it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models—and way, way more.

Unlike most machine learning books, the fully updated 2nd Edition of Machine Learning For Dummies doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study.

• Understand the history of AI and machine learning
• Work with Python 3.8 and TensorFlow 2.x (and R as a download)
• Build and test your own models
• Use the latest datasets, rather than the worn out data found in other books
• Apply machine learning to real problems

Whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.

C# is one of the most popular programming languages, and frequent updates help it keep pace as the world of coding changes. You can keep pace too, thanks to C# 10.0 All-in-One For Dummies, where you'll learn the basics of the language itself, how to code in Visual Studio, and how to take advantage of the new features in the latest release. At every stage of your career, you'll need to know the cutting-edge trends and techniques that clients want. This book has your back, with info on object-oriented programming, writing secure code, building web applications, and more.

The six standalone mini-books you'll find inside this all-in-one will take you through the changes to C# and the practical applications and dev tools that you need to know. New features covered include records, init only setters, top-level statements, pattern matching enhancements, fit and finish features, and a lot more. Plus, this version is packed with more examples and code snippets, so you can sharply see C# in action!

• Learn the very basics of C# programming, even if you have no prior experience
• Refresh your knowledge of the language and learn how to use the new features in the 10.0 version release
• Read six mini-books on hot coding topics like object-oriented programming, Visual Studio, and Windows 10 development
• Enhance your employability and join the 6.5-million-strong community of C# developers

You need an easy-to-read C# guide that will help you understand the incoming updates, and this For Dummies reference is it.

Un livre idéal pour serpenter pas à pas dans l'univers de la programmation en Python.
Ce livre permettra à tous les programmeurs débutants ou les étudiants en informatique de découvrir les bases de la programmation en Python, un langage qui peut-être utilisé seul ou avec un autre langage comme le C par exemple. Couvre la version 3 de Python.



Au programme :

Comprendre la syntaxe du langage Python
Concevoir des programmes et simplifier le développement
Blocs de données, chaînes et dictionnaires
S'initier à la programmation procédurale et orientée objet

Create simple, easy programs in the popular Python language 

Beginning Programming with Python For Dummies is the trusted way to learn the foundations of programming using the Python programming language. Python is one of the top-ranked languages, and there’s no better way to get started in computer programming than this friendly guide. You’ll learn the basics of coding and the process of creating simple, fun programs right away. This updated edition features new chapters, including coverage of Google Colab, plus expanded information on functions and objects, and new examples and graphics that are relevant to today’s beginning coders. Dummies helps you discover the wealth of things you can achieve with Python. 

• Employ an online coding environment to avoid installation woes and code anywhere, any time 
• Learn the basics of programming using the popular Python language 
• Create easy, fun projects to show off your new coding chops 
• Fix errors in your code and use Python with external data sets 

Beginning Programming with Python For Dummies will get new programmers started—the easy way. 

Un livre idéal pour serpenter pas à pas dans l'univers de la programmation en Python et en JavaScript
Ce livre 2 en 1 permettra à tous les programmeurs débutants ou les étudiants en informatique de découvrir les bases de la programmation en Python et en JavaScript. Deux langages souvent utilisés de concert notamment dans le développement d'applications de type machine learning.



Au programme :


Comprendre la syntaxe du langage Python


Concevoir des programmes et simplifier le développement


Blocs de données, chaînes et dictionnaires


S'initier à la programmation procédurale et orientée objet avec Python


Les concepts de la programmation JavaScript


Espionnage : détection du navigateur utilisé par vos visiteurs


La bonne cuisine des cookies


Images réactives et interactives


Les rollovers


Examen des saisies de l'utilisateur


Dynamisez vos pages

Your logical, linear guide to the fundamentals of data science programming

Data science is exploding—in a good way—with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models.

Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time.

• Get grounded: the ideal start for new data professionals
• What lies ahead: learn about specific areas that data is transforming  
• Be meaningful: find out how to tell your data story
• See clearly: pick up the art of visualization

Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s!

The fast and easy way to learn Python programming and statistics

Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. 

Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud.

• Get started with data science and Python
• Visualize information
• Wrangle data
• Learn from data

The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.

Modern businesses rely on Infrastructure-as-a-Service (IaaS)—a setup in which someone else foots the bill to create application environments—and developers are expected to know how to write both platform-specific and IaaS-supported applications. If you're a developer who writes desktop and web applications but have little-to-no experience with cloud development, this book is an essential tool in getting started in the IaaS environment with Amazon Web Services.

In Amazon Web Services For Developers For Dummies, you'll quickly and easily get up to speed on which language or platform will work best to meet a specific need, how to work with management consoles, ways you'll interact with services at the command line, how to create applications with the AWS API, and so much more.

• Assess development options to produce the kind of result that's actually needed
• Use the simplest approach to accomplish any given task
• Automate tasks using something as simple as the batch processing features offered by most platforms
• Create example applications using JavaScript, Python, and R
• Discover how to use the XML files that appear in the management console to fine tune your configuration

Making sense of Amazon Web Services doesn't have to be as difficult as it seems—and this book shows you how.

Focusing just on the essentials of command-line interface (CLI), Windows Command-Line Administration Instant Reference easily shows how to quickly perform day-to-day tasks of Windows administration without ever touching the graphical user interface (GUI). Specifically designed for busy administrators, Windows Command-Line Administration Instant Reference replaces many tedious GUI steps with just one command at the command-line, while concise, easy to access answers provide solutions on the spot.

• Provides practical examples, step-by-step instructions, and contextual information
• Quick-reference style delivers the commands needed for managing data and the network; working with Active Directory; performing diagnostics and maintenance; and, creating batch files and scripts
• Covers administration for Windows Server 2008 Server Core, Windows Server 2008 (including R2), and Windows 7

Administrators can get more done in less time with CLI than they can with the standard GUI. Compact enough to keep on hand at all times, Windows Command-Line Administration Instant Reference provides administrators with a convenient, fast and simple way to use CLI.

This plain-English guide gives you a thorough overview of LINQ, from understanding the tasks it performs to making LINQ work with both Visual Basic and Visual Studio 2005. It explains the four LINQ providers in the .NET Framework, the easiest ways to go about accessing data, and how to write more efficient applications with less code using LINQ. There’s also clear guidance on combining third-party providers with LINQ to create even more powerful apps. With this single, comprehensive guide, you’ll discover how to:

• Use one query language with all Microsoft languages
• Examine .NET language extensions and work with extension methods, partial methods, lambda expressions, and query expressions
• LINQ to DataSet operators, SQL server operations, XML API, or Active Directory
• Deal with databases — download and install the Northwind database, generate Northwind entity classes, and create the Northwind XML mapping file
• Create the partial class example, the partial method example, and the database modification example
• Use objects with LINQ
• Query databases in Visual Basic and C#

As an added bonus, you can visit the companion Web site for LINQ examples in C# and Visual Basic. With LINQ For Dummies, you’ll link up with LINQ in no time and see how you can query almost anything!

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

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 Description

Businesses 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 for

Whether 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.

Table of Contents

1. Defining Machine Learning Security
2. Mitigating Risk at Training by Validating and Maintaining Datasets
3. Mitigating Inference Risk by Avoiding Adversarial Machine Learning Attacks
4. Considering the Threat Environment
5. Keeping Your Network Clean
6. Detecting and Analyzing Anomalies
7. Dealing with Malware
8. Locating Potential Fraud
9. Defending against Hackers
10. Considering the Ramifications of Deepfakes
11. Leveraging Machine Learning against Hacking