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Lubanovic Bill: Introducing Python

Introducing Python

Modern Computing in Simple Packages

It's never too early to learn how to code! Coding For Kids For Dummies helps you learn the basics of coding the fun way. This book walks you through the essentials of coding with 12 exciting projects. You'll learn what coding is, how to make digital toys and games on your computer, and how to start writing your first lines of code! With step-by-step instructions and activities, this book makes it simple to get started. And when you see error messages, don't panic! All new coders make mistakes-this book helps you figure them out and fix them, so your code will be good to go. Along the way, you'll be boosting your creativity, getting better at logical thinking, and learning a skill that will open the door to fun hobbies and careers. So get coding! <ul> <li>Learn basic coding concepts and skills</li> <li>Create your own digital toys and games</li> <li>Figure out how to turn your ideas into code</li> <li>Get involved in the online coding community</li> </ul> Kids who want to learn how to code (and the parents who want to encourage them) can get off to a great start with Coding For Kids For Dummies.

Coding For Kids For Dummies

If you've been curious about artificial intelligence and machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning, 2nd Edition teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math - the book will cover the rest. After an introduction to Python, you'll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models' performance. You'll also learn: How to use classic machine learning models like k-Nearest Neighbours, Random Forests, and Support Vector Machines, How neural networks work and how they're trained, How to use convolutional neural networks, How to develop a successful deep learning model from scratch. You'll conduct experiments along the way, building to a final case study that incorporates everything you've learned. This second edition is thoroughly revised and updated, and adds six new chapters to further your exploration of deep learning from basic CNNs to more advanced models. New chapters cover fine tuning, transfer learning, object detection, semantic segmentation, multilabel classification, self-supervised learning, generative adversarial networks, and large language models. The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning, 2nd Edition will give you the skills and confidence to dive into your own machine learning projects.

A Python-Based Introduction

Practical Deep Learning, 2nd Edition

An application programming interface (API) enables data exchange in systems such as web applications, microservices, and IoT devices. In this hands-on book, authors Lukasz Dynowski and Marcin Dulak show software developers and architects how to design and implement REST, GraphQL, gRPC, webhooks, WebSocket, messaging APIs, and more. This book looks at the most popular API styles from a network, application, and architecture perspective. You'll learn how to determine the appropriate type of API for your application use case and how to tackle design decisions along the way. You'll also learn the trade-offs between various APIs and acquire practical knowledge of how to implement them. <ul><li>Explore the origins and evolution of API styles</li> <li>Learn network protocols that various APIs use</li> <li>Understand the trade-offs of each API style</li> <li>Select an appropriate API style</li> <li>Learn how to implement, secure, and document the APIs</li></ul>

Understanding the Trade-Offs of Common APIs and Choosing the Correct Solutions

Learning API Styles

Digital technology was supposed to change the world for the better, but it has left us miserable, divided and misinformed-when it hasn't posed a direct threat to our physical safety. As acclaimed writer Darryl Campbell explains, the problem isn't just greedy CEOs promising to "change the world" as they seek ever more eyeballs and app downloads. It's that the tech industry struggles to understand what its products actually do and how they might fail. The reason is twofold: an unshakeable faith in managerialism-the notion that every business can be reduced to a spreadsheet overseen by MBAs-and an equally strong belief in software as the solution to all problems. From aeroplane disasters to PowerPoint propaganda to the perils of generative AI, Campbell uncovers a pattern of recklessness and overconfidence in the managerial class-and ultimately argues that developers themselves must intervene to curb corporate power.

Why the Managerial Class Loses Control of Software

Fatal Abstraction

Is your frontend slowing down innovation and complicating team collaboration? Consider micro-frontends--a practical way to break development silos and accelerate feature delivery. In this updated second edition, software architects, tech leads, and software developers will learn how to design, build, and deploy independent micro-frontends that compose unique frontend systems. Author Luca Mezzalira, principal serverless specialist solutions architect at AWS, shows you how micro-frontends enable agility within an organization, decentralize decision-making, and optimize for fast flow. This gives your organization technical flexibility and allows you to hire and retain a broad spectrum of talent. Micro-frontends also support distributed or colocated teams more efficiently. Start transforming your frontend strategy today with proven techniques for speed of delivery, autonomy, and scale. <ul> <li>Accelerate delivery with four foundational pillars for micro-frontend success</li> <li>Apply actionable principles and best practices to empower your teams</li> <li>Navigate the benefits and pitfalls of micro-frontend architectures</li> <li>Integrate micro-frontends seamlessly with microservices and distributed systems</li> <li>Architect client-side and server-side micro-frontend solutions for maximum impact</li> </ul>

Distributed Systems for the Frontend

Building Micro-Frontends

Looking to accelerate development and build cloud native applications with AWS Cloud Development Kit? Through hands-on projects, you'll learn the basics of AWS CDK, the tool of choice for many of the world's largest technology companies. Informed by real case studies and years of work with enterprise-scale cloud architectures, this book will benefit both novice and advanced cloud developers. It's complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions to help you build a shareable portfolio of completed projects, demonstrating your ability to build cloud infrastructure at scale. You'll explore: <ul> <li>Basic cloud computing concepts, including the AWS Well-Architected Framework </li><li>End-to-end cloud native software and infrastructure as code </li><li>The benefits of a reusable code library to accelerate your projects </li><li>Functional modules of code that can stand alone or build toward an integrated cloud application </li></ul>

Building Cloud Native Applications with Infrastructure-As-Code

Hands-On AWS Cdk

THE #2 TIMES BESTSELLER'Artificial intelligence is going to have a massive impact on everyone's lives... an accessible and sensible read that helps demystify AI' Deborah Meaden, entrepreneur and star of Dragon's Den'Nigel Toon is a visionary leader in the field of artificial intelligence... a must-read' Marc Tremblay, Distinguished Engineer, MicrosoftThose who understand how AI thinks are about to win big. We are used to thinking of computers as being a step up from calculators - very good at storing information, and maybe even at playing a logical game like chess. But up to now they haven't been able to think in ways that are intuitive, or respond to questions as a human might. All that has changed, dramatically, in the past few years. Our search engines are becoming answer engines. Artificial intelligence is already revolutionising sectors from education to healthcare to the creative arts. But how does an AI understand sentiment or context? How does it play and win games that have an almost infinite number of moves? And how can we work with AI to produce insights and innovations that are beyond human capacity, from writing code in an instant to unfolding the elaborate 3D puzzles of proteins?We stand at the brink of a historic change that will disrupt society and at the same time create enormous opportunities for those who understand how AI thinks. Nigel Toon shows how we train AI to train itself, so that it can paint images that have never existed before or converse in any language. In doing so he reveals the strange and fascinating ways that humans think, too, as we learn how to live in a world shared by machine intelligences of our own creation.

How we built it, how it can help us, and how we can control it

How AI Thinks

Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

This book is designed to cater to readers who prefer a hands-on guide using SPSS Modeler, a widely popular software that does not require coding or programming skills. It targets a broad audience, including students, lecturers, researchers, and industry professionals.

Data Science and Machine Learning Using IBM SPSS Modeler

Demystifying AI

This concise yet comprehensive guide shows developers and architects how to tackle data integration challenges with MuleSoft. Authors Pooja Kamath and Diane Kesler take you through the process necessary to build robust and scalable integration solutions step-by-step. Supported by real-world use cases, Building Integrations with MuleSoft teaches you to identify and resolve performance bottlenecks, handle errors, and ensure the reliability and scalability of your integration solutions. You'll explore MuleSoft's robust set of connectors and their components, and use them to connect to systems and applications from legacy databases to cloud services. <ul> <li>Ask the right questions to determine your use case, define requirements, decide on reuse versus rebuild, and create sequence and context diagrams </li><li>Master tools like the Anypoint Platform, Anypoint Studio, Code Builder, GitHub, and Maven </li><li>Design APIs with RAML and OAS and craft effective requests and responses </li><li>Write MUnit tests, validate DataWeave expressions, and use Postman Collections </li><li>Deploy Mule applications to CloudHub, use API Manager to create API proxies, and secure APIs with Mule OAuth 2.0 </li><li>Learn message orchestration techniques for routers, transactions, error handling, For Each, Parallel For Each, and batch processing </li></ul>

Integrating Systems and Unifying Data in the Enterprise

Building Integrations with Mulesoft

This book provides readers with the concepts and tools necessary to bring a robot to life through programming. It will equip them with the skills necessary to undertake projects with ROS2, the new version of ROS, with no previous experience with ROS2 needed.

A Concise Introduction to Robot Programming with ROS 2

Your Python code may run correctly, but what if you need it to run faster? This practical book shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By explaining the fundamental theory behind design choices, this expanded edition of High Performance Python helps experienced Python programmers gain a deeper understanding of Python's implementation. How do you take advantage of multicore architectures or compilation? Or build a system that scales up beyond RAM limits or with a GPU? Authors Micha Gorelick and Ian Ozsvald reveal concrete solutions to many issues and include war stories from companies that use high-performance Python for GenAI data extraction, productionized machine learning, and more. <ul> <li>Get a better grasp of NumPy, Cython, and profilers</li> <li>Learn how Python abstracts the underlying computer architecture</li> <li>Use profiling to find bottlenecks in CPU time and memory usage</li> <li>Write efficient programs by choosing appropriate data structures</li> <li>Speed up matrix and vector computations</li> <li>Process DataFrames quickly with Pandas, Dask, and Polars</li> <li>Speed up your neural networks and GPU computations</li> <li>Use tools to compile Python down to machine code</li> <li>Manage multiple I/O and computational operations concurrently</li> <li>Convert multiprocessing code to run on local or remote clusters</li> </ul>

Practical Performant Programming for Humans

High Performance Python

Master the inner workings of your x64 Linux system and expand your OS expertise by writing your very own debugger using C++. If debuggers seem like magic to you, there is no better way to demystify them than to write your own. This book will show you exactly how to do it, walking you through the entire process of building a debugger for x64 Linux systems using C++. As go from an empty filesystem folder to a fully fledged debugger capable of setting breakpoints, stepping through code, manipulating variables, and more, you’ll learn how to: <ul><li>Attach to a process</li><li>Read and write to registers</li><li>Set hardware and software breakpoints</li><li>Output disassembly</li><li>Support multithreading and other tasks</li></ul> As you add features to your debugger, you’ll also pick up a wealth of knowledge about operating systems, compilers, software testing, and low-level programming that you can use in your day-to-day development.

Building a Debugger

Introducing Python

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