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Learn Python Programming
Get up and running with Python 3.9 through concise tutorials and practical projects in this fully updated third edition.Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesExtensively revised with richer examples, Python 3.9 syntax, and new chapters on APIs and packaging and distributing Python codeDiscover how to think like a Python programmerLearn the fundamentals of Python through real-world projects in API development, GUI programming, and data scienceBook DescriptionLearn Python Programming, Third Edition is both a theoretical and practical introduction to Python, an extremely flexible and powerful programming language that can be applied to many disciplines. This book will make learning Python easy and give you a thorough understanding of the language. You'll learn how to write programs, build modern APIs, and work with data by using renowned Python data science libraries. This revised edition covers the latest updates on API management, packaging applications, and testing. There is also broader coverage of context managers and an updated data science chapter. The book empowers you to take ownership of writing your software and become independent in fetching the resources you need. You will have a clear idea of where to go and how to build on what you have learned from the book. Through examples, the book explores a wide range of applications and concludes by building real-world Python projects based on the concepts you have learned.What you will learnGet Python up and running on Windows, Mac, and LinuxWrite elegant, reusable, and efficient code in any situationAvoid common pitfalls like duplication, complicated design, and over-engineeringUnderstand when to use the functional or object-oriented approach to programmingBuild a simple API with FastAPI and program GUI applications with TkinterGet an initial overview of more complex topics such as data persistence and cryptographyFetch, clean, and manipulate data, making efficient use of Python’s built-in data structuresWho this book is forThis book is for everyone who wants to learn Python from scratch, as well as experienced programmers looking for a reference book. Prior knowledge of basic programming concepts will help you follow along, but it’s not a prerequisite.
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Eye-Tracking with Python and Pylink
Several Python programming books feature tools designed for experimental psychologists. What sets this book apart is its focus on eye-tracking.Eye-tracking is a widely used research technique in psychology and neuroscience labs. Research grade eye-trackers are typically faster, more accurate, and of course, more expensive than the ones seen in consumer goods or usability labs. Not surprisingly, a successful eye-tracking study usually requires sophisticated computer programming. Easy syntax and flexibility make Python a perfect choice for this task, especially for psychology researchers with little or no computer programming experience.This book offers detailed coverage of the Pylink library, a Python interface for the gold standard EyeLink ® eye-trackers, with many step-by-step example scripts. This book is a useful reference for eye-tracking researchers, but you can also use it as a textbook for graduate-level programming courses.
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Python GUI Programming with Tkinter
Transform your evolving user requirements into feature-rich Tkinter applicationsKey FeaturesExtensively revised with new content on RESTful networking, classes in Tkinter, and the Notebook widgetTake advantage of Tkinter’s lightweight, portable, and easy-to-use featuresBuild better-organized code and learn to manage an evolving codebaseBook DescriptionTkinter is widely used to build GUIs in Python due to its simplicity. In this book, you’ll discover Tkinter’s strengths and overcome its challenges as you learn to develop fully featured GUI applications.Python GUI Programming with Tkinter, Second Edition, will not only provide you with a working knowledge of the Tkinter GUI library, but also a valuable set of skills that will enable you to plan, implement, and maintain larger applications. You’ll build a full-blown data entry application from scratch, learning how to grow and improve your code in response to continually changing user and business needs.You’ll develop a practical understanding of tools and techniques used to manage this evolving codebase and go beyond the default Tkinter widget capabilities. You’ll implement version control and unit testing, separation of concerns through the MVC design pattern, and object-oriented programming to organize your code more cleanly.You’ll also gain experience with technologies often used in workplace applications, such as SQL databases, network services, and data visualization libraries. Finally, you’ll package your application for wider distribution and tackle the challenge of maintaining cross-platform compatibility.What you will learnProduce well-organized, functional, and responsive GUI applicationsExtend the functionality of existing widgets using classes and OOPPlan wisely for the expansion of your app using MVC and version controlMake sure your app works as intended through widget validation and unit testingUse tools and processes to analyze and respond to user requestsBecome familiar with technologies used in workplace applications, including SQL, HTTP, Matplotlib, threading, and CSVUse PostgreSQL authentication to ensure data security for your applicationWho this book is forThis book is for programmers who understand the syntax of Python, but do not yet have the skills, techniques, and knowledge to design and implement a complete software application. A fair grasp of basic Python syntax is required.
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Thermal Physics Tutorials with Python Simulations
This book provides an accessible introduction to thermal physics with computational approaches that complement the traditional mathematical treatments of classical thermodynamics and statistical mechanics. It guides readers through visualizations and simulations in the Python programming language, helping them to develop their own technical computing skills (including numerical and symbolic calculations, optimizations, recursive operations, and visualizations). Python is a highly readable and practical programming language, making this book appropriate for students without extensive programming experience.This book may serve as a thermal physics textbook for a semester-long undergraduate thermal physics course or may be used as a tutorial on scientific computing with focused examples from thermal physics. This book will also appeal to engineering students studying intermediate-level thermodynamics as well as computer science students looking to understand how to apply their computer programming skills to science.Key features Major concepts in thermal physics are introduced cohesively through computational and mathematical treatments. Computational examples in Python programming language guide students on how to simulate and visualize thermodynamic principles and processes for themselves.
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Programming the Intel Edison: Getting Started with Processing and Python
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Learn To Easily Create Robotic, IoT, and Wearable Electronic Gadgets!Get up-and-running building cutting-edge Edison devices with help from this DIY guide. Programming the Intel Edison: Getting Started with Processing and Python lays out the Edison’s powerful features and teaches the basics of Internet-enabled embedded programming. Discover how to set up components, connect your PC or Mac, build Python applications, and use USB, WiFi, and Bluetooth connections. Start-to-finish example projects include a motor controller, home temperature system, robotic car, and wearable hospital alert sensor.Explore the capabilities and features of the EdisonConnect Sparkfun, Break-out, and Arduino boardsProgram your Edison through the Arduino IDESet up USB, GPIO, WiFi, and Bluetooth connections
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Learning Python with Raspberry Pi
The must-have companion guide to the Raspberry Pi User Guide! Raspberry Pi chose Python as its teaching language of choice to encourage a new generation of programmers to learn how to program. This approachable book serves as an ideal resource for anyone wanting to use Raspberry Pi to learn to program and helps you get started with the Python programming language. Aimed at first-time developers with no prior programming language assumed, this beginner book gets you up and running. Covers variables, loops, and functionsAddresses 3D graphics programmingWalks you through programming MinecraftZeroes in on Python for scripting Learning Python with Raspberry Pi proves itself to be a fantastic introduction to coding.
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Code the Classics Volume II
Take inspiration from the some of the greatest video games of the 1980s and learn how to write your own modern classicsCode the Classics Volume II not only tells the stories of some of the seminal video games of the 1980s, but shows you how to create your own games inspired by them, following examples programmed by Raspberry Pi founder Eben Upton. In this book, you'll learn how to run and edit the games in this book by installing Python, Pygame Zero, and an IDE. You'll also:Get game design tips and tricks from the masters.Understand the fundamental tasks needed for every game: display images, play sound effects and receive inputs from the keyboard or a game controller.Learn how to code your own games with Pygame Zero, a library that helps automate those tasks.Explore the code listings and find out how they work.You'll meet these vintage-inspired games, and learn from their code in between rounds of play:Avenger: fly across a scrolling landscape while you save humans from malevolent aliens.Beat Streets: fight your way through a level, and defeat a notorious crime boss.Eggzy: collect gems and survive as long as possible before time runs out.Leading Edge: Race a car on a pseudo-3d race track.Kinetix: Break bricks with your paddle, and use powerups to avoid various menaces.
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Programming in Two Semesters
This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts.The first part, which teaches Python, covers fundamental programming concepts, such as data types and control structures and functions. It introduces more complex data types such as lists and dictionaries and also deals with file handling. It introduces object-oriented concepts and ends with a case study bringing together all the topics of the first semester. The second part uses Java to teach advanced concepts and centres around object-oriented programming, teaching key object-oriented concepts such as inheritance and polymorphism. The semester again ends with an advanced case study bringing together all the topics of the second semester.Topics and features:Assumes no prior knowledge, and makes the transition from Python to Java a smooth processFeatures numerous exercises and also an illustrative case study for each language Examines procedural and object-oriented methodologies, as well as design principles Covers such advanced topics as interfaces and lambda expressions, exceptions and Collections Includes a chapter on graphics programming in Python using Tkinter Introduces the latest Java technology for graphical interfaces, JavaFXExplains design concepts using UML notation Offering a gentle introduction to the field and assuming no prerequisite background, Programming in Two Semesters is the ideal companion to undergraduate modules in software development or programming. In addition, it will serve as a strong primer for professionals looking to strengthen their knowledge of programming with these languages.
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Internet of Things Programming Projects
A practical project-based guide to help you build and control your IoT projectsKey FeaturesLeverage the full potential of IoT with the combination of Raspberry Pi 3 and PythonBuild complex Python-based applications with IoTWork on various IoT projects and understand the basics of electronicsBook DescriptionThe Internet of Things (IOT) has managed to attract the attention of researchers and tech enthusiasts, since it powerfully combines classical networks with instruments and devices.In Internet of Things Programming Projects, we unleash the power of Raspberry Pi and Python to create engaging projects. In the first part of the book, you’ll be introduced to the Raspberry Pi, learn how to set it up, and then jump right into Python programming. Then, you’ll dive into real-world computing by creating a“Hello World” app using flash LEDs.As you make your way through the chapters, you’ll go back to an age when analog needle meters ruled the world of data display. You’ll learn to retrieve weather data from a web service and display it on an analog needle meter, and build a home security system using the Raspberry Pi. The next project has a modern twist, where we employ the Raspberry Pi to send a signal to a web service that will send you a text when someone is at the door. In the final project, you take what you've learned from the previous two projects and create an IoT robot car that you can use to monitor what your pets are up to when you are away.By the end of this book, you will be well versed in almost every possible way to make your IoT projects stand out.What you will learnInstall and set up a Raspberry Pi for IoT developmentLearn how to use a servo motor as an analog needle meter to read dataBuild a home security dashboard using an infrared motion detectorCommunicate with a web service that sends you a message when the doorbell ringsReceive data and display it with an actuator connected to the Raspberry PiBuild an IoT robot car that is controlled through the internetWho this book is forInternet of Things Programming Projects is for Python developers and programmers who are interested in building their own IoT applications and IoT-based projects. It is also targeted at IoT programmers and developers who are looking to build exciting projects with Python.
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Physics with Excel and Python
This book is intended to serve as a basic introduction to scientific computing by treating problems from various areas of physics - mechanics, optics, acoustics, and statistical reasoning in the context of the evaluation of measurements. After working through these examples, students are able to independently work on physical problems that they encounter during their studies. For every exercise, the author introduces the physical problem together with a data structure that serves as an interface to programming in Excel and Python. When a solution is achieved in one application, it can easily be translated into the other one and presumably any other platform for scientific computing. This is possible because the basic techniques of vector and matrix calculation and array broadcasting are also achieved with spreadsheet techniques, and logical queries and for-loops operate on spreadsheets from simple Visual Basic macros. So, starting to learn scientific calculation with Excel, e.g., at High School, is a targeted road to scientific computing. The primary target groups of this book are students with a major or minor subject in physics, who have interest in computational techniques and at the same time want to deepen their knowledge of physics. Math, physics and computer science teachers and Teacher Education students will also find a companion in this book to help them integrate computer techniques into their lessons. Even professional physicists who want to venture into Scientific Computing may appreciate this book.
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Mastering OpenCV 4 with Python
Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality.Key FeaturesDevelop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4) and PythonApply machine learning and deep learning techniques with TensorFlow and KerasDiscover the modern design patterns you should avoid when developing efficient computer vision applicationsBook DescriptionOpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language.In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras.By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands.What you will learnHandle files and images, and explore various image processing techniquesExplore image transformations, including translation, resizing, and croppingGain insights into building histogramsBrush up on contour detection, filtering, and drawingWork with Augmented Reality to build marker-based and markerless applicationsWork with the main machine learning algorithms in OpenCVExplore the deep learning Python libraries and OpenCV deep learning capabilitiesCreate computer vision and deep learning web applicationsWho this book is forThis book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.
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50 Algorithms Every Programmer Should Know - Second Edition
Delve into the realm of generative AI and large language models (LLMs) while exploring modern deep learning techniques, including LSTMs, GRUs, RNNs with new chapters included in this 50% new edition overhaulPurchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesFamiliarize yourself with advanced deep learning architecturesExplore newer topics, such as handling hidden bias in data and algorithm explainabilityGet to grips with different programming algorithms and choose the right data structures for their optimal implementationBook DescriptionThe ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works.You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them.Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use.You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT.Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.What you will learnDesign algorithms for solving complex problemsBecome familiar with neural networks and deep learning techniquesExplore existing data structures and algorithms found in Python librariesImplement graph algorithms for fraud detection using network analysisDelve into state-of-the-art algorithms for proficient Natural Language Processing illustrated with real-world examplesCreate a recommendation engine that suggests relevant movies to subscribersGrasp the concepts of sequential machine learning models and their foundational role in the development of cutting-edge LLMsWho this book is forThis computer science book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code.Whether you are a beginner looking to learn the most used algorithms concisely or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful.Python programming experience is a must, knowledge of data science will be helpful but not n
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Hands-on Signal Analysis with Python
This book provides the tools for analyzing data in Python: different types of filters are introduced and explained, such as FIR-, IIR- and morphological filters, as well as their application to one- and two-dimensional data. The required mathematics are kept to a minimum, and numerous examples and working Python programs are included for a quick start. The goal of the book is to enable also novice users to choose appropriate methods and to complete real-world tasks such as differentiation, integration, and smoothing of time series, or simple edge detection in images. An introductory section provides help and tips for getting Python installed and configured on your computer. More advanced chapters provide a practical introduction to the Fourier transform and its applications such as sound processing, as well as to the solution of equations of motion with the Laplace transform. A brief excursion into machine learning shows the powerful tools that are available with Python. This book also provides tips for an efficient programming work flow: from the use of a debugger for finding mistakes, code-versioning with git to avoid the loss of working programs, to the construction of graphical user interfaces (GUIs) for the visualization of data. Working, well-documented Python solutions are included for all exercises, and IPython/Jupyter notebooks provide additional help to get people started and outlooks for the interested reader.
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Programming with MicroPython
It’s an exciting time to get involved with MicroPython, the re-implementation of Python 3 for microcontrollers and embedded systems. This practical guide delivers the knowledge you need to roll up your sleeves and create exceptional embedded projects with this lean and efficient programming language. If you’re familiar with Python as a programmer, educator, or maker, you’re ready to learn—and have fun along the way. Author Nicholas Tollervey takes you on a journey from first steps to advanced projects. You’ll explore the types of devices that run MicroPython, and examine how the language uses and interacts with hardware to process input, connect to the outside world, communicate wirelessly, make sounds and music, and drive robotics projects. Work with MicroPython on four typical devices: PyBoard, the micro:bit, Adafruit’s Circuit Playground Express, and ESP8266/ESP32 boards Explore a framework that helps you generate, evaluate, and evolve embedded projects that solve real problems Dive into practical MicroPython examples: visual feedback, input and sensing, GPIO, networking, sound and music, and robotics Learn how idiomatic MicroPython helps you express a lot with the minimum of resources Take the next step by getting involved with the Python community
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Introduction to Scientific Computing with MATLAB® and Python Tutorials
This textbook is written for the first introductory course on scientific computing. It covers elementary numerical methods for linear systems, root finding, interpolation, numerical integration, numerical differentiation, least squares problems, initial value problems and boundary value problems. It includes short Matlab and Python tutorials to quickly get students started on programming. It makes the connection between elementary numerical methods with advanced topics such as machine learning and parallel computing.This textbook gives a comprehensive and in-depth treatment of elementary numerical methods. It balances the development, implementation, analysis and application of a fundamental numerical method by addressing the following questions.•Where is the method applied?•How is the method developed?•How is the method implemented?•How well does the method work?The material in the textbook is made as self-contained and easy-to-follow as possible with reviews and remarks. The writing is kept concise and precise. Examples, figures, paper-and-pen exercises and programming problems are deigned to reinforce understanding of numerical methods and problem-solving skills.
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Numerical Methods in Physics with Python
Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject.
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Python Programming for Mathematics
Python Programming for Mathematics focuses on the practical use of the Python language in a range of different areas of mathematics. Through fifty-five exercises of increasing difficulty, the book provides an expansive overview of the power of using programming to solve complex mathematical problems.This book is intended for undergraduate and graduate students who already have learned the basics of Python programming and would like to learn how to apply that programming skill in mathematics.FeaturesInnovative style that teaches programming skills via mathematical exercises.Ideal as a main textbook for Python for Mathematics courses, or as a supplementary resource for Numerical Analysis and Scientific Computing courses.
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OpenCV 4 with Python Blueprints
Get to grips with traditional computer vision algorithms and deep learning approaches, and build real-world applications with OpenCV and other machine learning frameworksKey FeaturesUnderstand how to capture high-quality image data, detect and track objects, and process the actions of animals or humansImplement your learning in different areas of computer visionExplore advanced concepts in OpenCV such as machine learning, artificial neural network, and augmented realityBook DescriptionOpenCV is a native cross-platform C++ library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. This book will get you hands-on with a wide range of intermediate to advanced projects using the latest version of the framework and language, OpenCV 4 and Python 3.8, instead of only covering the core concepts of OpenCV in theoretical lessons. This updated second edition will guide you through working on independent hands-on projects that focus on essential OpenCV concepts such as image processing, object detection, image manipulation, object tracking, and 3D scene reconstruction, in addition to statistical learning and neural networks.You’ll begin with concepts such as image filters, Kinect depth sensor, and feature matching. As you advance, you’ll not only get hands-on with reconstructing and visualizing a scene in 3D but also learn to track visually salient objects. The book will help you further build on your skills by demonstrating how to recognize traffic signs and emotions on faces. Later, you’ll understand how to align images, and detect and track objects using neural networks.By the end of this OpenCV Python book, you’ll have gained hands-on experience and become proficient at developing advanced computer vision apps according to specific business needs.What you will learnGenerate real-time visual effects using filters and image manipulation techniques such as dodging and burningRecognize hand gestures in real-time and perform hand-shape analysis based on the output of a Microsoft Kinect sensorLearn feature extraction and feature matching to track arbitrary objects of interestReconstruct a 3D real-world scene using 2D camera motion and camera reprojection techniquesDetect faces using a cascade classifier and identify emotions in human faces using multilayer perceptronsClassify, localize, and detect objects with deep neural networksWho this book is forThis book is for intermediate-level OpenCV users who are looking to enhance their skills by developing advanced applications. Familiarity with OpenCV concepts and Python libraries, and basic knowledge of the Python programming language are assumed.
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Design Multi-Agent AI Systems Using MCP and A2A
Build a production-ready multi-agent AI framework from scratch using MCP and A2A to orchestrate powerful agent workflowsFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild Python-based AI agents without relying on third-party orchestration frameworksDesign production-ready multi-agent systems using A2A messagingIntegrate memory and context with MCP to create adaptive and stateful agentic AI frameworksBook DescriptionFrustrated by opaque agent frameworks that hide how things work? This book gives you complete control by guiding you through building a fully functional, extensible agentic AI framework in Python without relying on external orchestration tools.You’ll begin by implementing a simple tool-using agent, and then gradually extend its capabilities with structured tool schemas, user interfaces, and memory via the Model Context Protocol (MCP). From there, you’ll build collaborative multi-agent systems powered by Agent-to-Agent (A2A) messaging and deploy them in realistic environments. Along the way, you’ll explore secure tool invocation, message routing, observability, and human-in-the-loop workflows.With annotated code, deep engineering insights, and practical deployment patterns, this hands-on guide equips you to build AI agents that reason, plan, act, and adapt, whether you’re shipping production systems or experimenting with cutting-edge LLM-based architectures.Written by Gigi Sayfan, who builds AI agent infrastructure at Perplexity and is a bestselling author with decades of experience in AI and distributed systems, this book gives you the tools and knowledge to engineer your own advanced agentic systems.*Email sign-up and proof of purchase requiredWhat you will learnDesign and implement tool-using AI agents from the ground upBuild modular components for extensible agent frameworksCreate secure and observable tools with structured inputsIntegrate agents with chat UIs such as Slack and ChainlitLeverage MCP for context handling and agent memoryOrchestrate collaborative agent workflows using A2ADebug and deploy agents in production-like environmentsExplore future-ready agent capabilities and GenUX designWho this book is forThis book is essential for AI engineers, ML practitioners, and software architects building agentic systems with large language models. It’s also ideal for DevOps engineers and technical leaders seeking deep insights into building and scaling autonomous AI workflows. Python coding skills and basic familiarity with LLMs are recommended.
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