{"title":"STEM \u0026 STEAM eBooks: Coding, Robotics \u0026 Maker Guides","description":null,"products":[{"product_id":"3d-printing-with-autodesk-123d-tinkercad-and-makerbot-9780071833486","title":"3D Printing with Autodesk 123D, Tinkercad, and MakerBot","description":"Master the art of 3D printing with step-by-step tutorials and DIY projects Are you ready to join the new industrial revolution? 3D Printing with Autodesk 123D, Tinkercad, and MakerBot reveals how to turn your ideas into physical products that you can use or sell! You'll learn how tooperate powerful, free software from Autodesk and bring your creations to life with the MakerBot--a leading consumer printer--or an online service bureau. Practical examples take you through the Design, Catch, Meshmixer, Tinkercad, Make, and CNC Utility apps, and the MakerBot Desktop. Fun projects, easy-to-follow instructions, and clear screenshots progress from installing the software to printing the design. 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While there are many other resources that cover the general process of 3D printing, this book is the ultimate guide to creating models for 3D printing using SketchUp.\nYou’ll start with a basic understanding of how SketchUp is used in the 3D printing workflow and jump into the steps to create a print-ready model using only SketchUp. This 3D printing book will guide you in using SketchUp to modify existing 3D files and cover additional tools that make SketchUp an even more powerful modeling tool. 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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!  \u003c\/p\u003e\u003cul\u003e  \u003cli\u003eLearn basic coding concepts and skills\u003c\/li\u003e  \u003cli\u003eCreate your own digital toys and games\u003c\/li\u003e  \u003cli\u003eFigure out how to turn your ideas into code\u003c\/li\u003e  \u003cli\u003eGet involved in the online coding community\u003c\/li\u003e  \u003c\/ul\u003e  \u003cp\u003eKids who want to learn how to code (and the parents who want to encourage them) can get off to a great start with \u003ci\u003eCoding For Kids For Dummies.\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eNote:\u003c\/strong\u003e This is a digital eBook. 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This book provides prospective allied health professionals with everything they need to know to get started in medical billing and coding as a career. In addition to an introduction to the basics of medical coding, you'll get information on how to find a training course, meet certification requirements, and deal with government agencies and insurance companies. Learn about the standard practices in the medical billing industry and get up to speed on the ethical and legal issues you're likely to face on the job. This accessible guide is a great entry point—and a great refresher—for anyone interested in the medical billing and coding profession. 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He can't talk to anyone outside, and the only way to communicate is through the robot. Inside the robot, Kai finds many books and documents written in a strange language—it's the robot's language, which is Python. Kai realizes he needs to learn this language to control the robot and talk to the outside world. In each chapter in this book, we will join Kai on a new adventure to learn something that helps us control the robot better and communicate with the real world. This fun and interactive book is designed to introduce young minds to the basics of programming while encouraging creativity and problem-solving skills.    In the introductory chapters, readers discover Python as a friendly and accessible programming language. The book guides them through setting up their programming environment and crafting their initial lines of code, laying the foundation for an exciting coding adventure. As the exploration unfolds, it delves into fundamental programming concepts essential for any budding coder. From variables and data types to loops and conditionals, these building blocks empower readers to create their programs, fostering a solid understanding of the core principles of coding. It seamlessly integrates these concepts with previously learned fundamentals, providing a comprehensive view of Python's capabilities. Fueling creativity, it inspires readers to unleash their imagination through engaging projects. 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[Ultimate Robotics Programming with ROS 2 and Python] introduces readers to ROS 2 without requiring prior experience in robotics. It blends theoretical explanations with practical exercises, empowering readers to solve specific robotics problems while understanding the reasoning behind various approaches.\n\nThe book covers a broad spectrum of robotics topics, including mobile robots, industrial manipulators, and aerial robots. These systems are simulated using the modern Gazebo simulator and programmed with ROS 2’s out-of-the-box tools and custom solutions using the ROS 2 API. The book also delves into computer vision, generative AI, and machine learning, providing hands-on examples of real-world applications.\n\nWith intermediate challenges designed to reinforce learning, this book serves as an all-encompassing guide for anyone looking to master robotics programming with ROS 2 and Python. Step into the future of robotics and gain the expertise to build sophisticated, real-world robotic systems that can tackle the complex challenges of tomorrow.\n\nWhat you will learn\n● Understand the fundamentals of ROS 2 for robotics development.\n● Develop robotics applications using Python and ROS 2 programming.\n● Master advanced ROS 2 packages for navigation and manipulation.\n● Implement behavior trees in ROS 2 with Python for intelligent robots.\n● Utilize modern Gazebo for realistic robot simulation with ROS 2.\n● Integrate Large Language Models (LLMs) with ROS 2 for advanced functionalities.\n● Perform computer vision tasks with ROS 2 for intelligent robots.\n\nTable of Contents\n1. Introduction to Robot Operating System 2\n2. Hands-on ROS 2 Programming Using Python\n3. Supplementary Tools for ROS 2\n4. Robot Visualization and Simulation\n5. Writing Tests Using Pytest for ROS 2 Nodes\n6. Controlling an Inverted Pendulum with a PID Controller\n7. Laser-based Obstacle Avoidance with a Wheeled Mobile Robot\n8. ROS 2 Behaviour Trees Using Python\n9. Surveillance System Using Behaviour Trees\n10. Robot Navigation Using ROS 2 Navigation Stack (Nav2)\n11. Robot Arm Control Using MoveIt 2\n12. Programming Aerial Robots Using ROS 2\n13. Computer Vision Using ROS 2\n14. Object Detection Using ROS 2\n15. Using Large Language Models with ROS 2\n16. Deep Reinforcement Learning Using ROS 2\nIndex\n\nAbout the Authors\nJonathan Cacace was born in Naples, Italy, on 13 December 1987. He holds a Bachelor’s and Master’s of Science in Computer Science from University of Naples “Federico II”. Later he joined the PhD program of the same institution, earning the title of Philosophiae Doctor in Automation and Computer Engineering in 2016.\n\nDuring his research career, he had the chance to participate and lead various applied research projects focused on robotics, funded by the European Union. This allowed him to explore several areas of robotics, from robot manipulation to navigation. After completing his PhD, he continued to divide his work between scientific research and applied robotics, participating in more than 50 scientific publications in the flagship robotics conferences and scientific journals. He also collaborated as a private consultant for different startups based in Europe.\u003cp\u003e\u003cstrong\u003eNote:\u003c\/strong\u003e This is a digital eBook. You will receive instant access after purchase. 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Start by creating a system to detect movement with a PIR motion sensor and a Raspberry Pi board. Use the MQ2 gas sensor and a Raspberry Pi board as a gas leak alarm system to detect dangerous explosive and fire hazards. Then train your system to send the captured data to the remote server ThingSpeak. You’ll also develop a weather station with your Raspberry Pi. Using the DHT11 (humidity and temperature sensor) and BMP (barometric pressure and temperature sensor) in conjunction with ThingSpeak and X, you can receive real time weather alerts from your own meterological system! Spectral sensers used with the Raspberry Pi include the AS7262 (six colors), and AS7263 (near infrared) for the construction of a filter spectrometer, sensing colored solutions, and assessing plant foliage health. Finally, expand your skills into the popular machine learning world of digital image processing using OpenCV and a Pi. 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The new edition is 64-bit, based on the latest Raspberry Pi OS and hardware, and incorporates reader feedback from the first edition. What You'll Learn Program basic ARM 64-Bit Assembly Language Interface with the various hardware devices on the Raspberry Pi Comprehend code containing Assembly Language Use the official ARM reference documentation     Who This Book Is For Coders who have already learned to program in a higher-level language like Python, Java, C#, or C and now wish to learn Assembly Language programming.\u003cp\u003e\u003cstrong\u003eNote:\u003c\/strong\u003e This is a digital eBook. You will receive instant access after purchase. 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Particularly suited to people who are not programmers by trade; the material introduces Python basics rather than assuming a professional programming background.","brand":"ThinkEDU","offers":[{"title":"Default Title","offer_id":60814862713118,"sku":"9781808761362","price":44.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0800\/4435\/9966\/files\/1024_13814189-f692-4c7c-bb11-83674ea9b83a.jpg?v=1793745474"},{"product_id":"python-3-9781493228010","title":"Python 3","description":"Ready to master Python? In this updated edition of the prize-winning Python reference, learn to write effective code, whether you’re a beginner or a professional programmer. Review core Python concepts, including functions, modularization, and object orientation, and walk through the available data types. Then dive into more advanced topics, such as exception handling, static type checking, and regular expressions. 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Starting with the fundamentals, you’ll learn how to characterize datasets, measure and validate prediction performance, engineer features, and build forecasting pipelines.\nThe book covers classical methods such as ARIMA and Theta, machine learning methods such as gradient boosting, and deep learning with recurrent, latest Transformer-based (like Crossformer), or convolutional (TimesNet) models. We'll apply foundation models such as TimesFM, Chronos, and OpenTSLM, or generative approaches like Chain-of-Charts, and uncertainty quantification with conformal prediction such as GARCH conformal, conformalized quantile regression, or split conformal. We’ll also dive into production infrastructure like feature stores, model tracking, and monitoring and scaling strategies, as well as classification, self-supervised encoding, spatiotemporal modeling, handling irregular time series with ODEs, survival analysis, and causal inference.\nThrough practical examples, you’ll learn how to evaluate models, detect and handle anomalies and drift, and choose approaches that match data and operational needs.\u003ch4\u003eWhat you will learn\u003c\/h4\u003e\u003cul\u003e\n\u003cli\u003eApply classical time series models such as ETS, ARIMA, and Theta\u003c\/li\u003e\n\u003cli\u003eValidate with SMAPE, MASE, RMSSE and rolling window, and walk-forward\u003c\/li\u003e\n\u003cli\u003eForecast as regression with sktime, darts, mlforecast, and skforecast\u003c\/li\u003e\n\u003cli\u003eUse modern deep learning like LSTMs, DLinear, TSMixer, and TimesNet\u003c\/li\u003e\n\u003cli\u003eGrasp foundation models such as TimesFM, OpenTSLM, or Chain-of-Charts\u003c\/li\u003e\n\u003cli\u003eQuantify uncertainty quantification with conformalized regression\u003c\/li\u003e\n\u003cli\u003eSet up feature stores, MLflow, and monitoring and scaling strategies\u003c\/li\u003e\n\u003cli\u003eHandle classification, drift, spatiotemporal and irregular time series\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4\u003eWho this book is for\u003c\/h4\u003eThis book is ideal for data analysts, data scientists, and Python developers who want instantly useful and practical recipes to implement today, and a comprehensive reference book for tomorrow. 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This book brings those foundations into one practical progression, helping you connect the concepts behind machine learning with the code used to build models.\n\nYou will start with Python programming, NumPy, Pandas, data visualization, exploratory data analysis, linear algebra, calculus, probability, and statistics. From there, you will build supervised learning skills across regression, classification, k-NN, feature engineering, model evaluation, cross-validation, and hyperparameter tuning. You will then work with ensemble methods including random forests, gradient boosting, XGBoost, LightGBM, and CatBoost, while learning to handle imbalanced data and justify modeling decisions.\n\nThe final part moves into neural networks and deep learning with TensorFlow, Keras, and PyTorch. You will build CNNs for image classification, explore RNNs, LSTMs, GRUs, word embeddings, and sequence-to-sequence models, and understand attention and transformer architectures through BERT and GPT examples. You will finish by applying transfer learning and fine-tuning to computer vision and NLP tasks, supported by projects that turn theory into practical AI and machine learning skills for real-world problem solving.\u003ch4\u003eWhat you will learn\u003c\/h4\u003e\u003cul\u003e\n\u003cli\u003eUse Python, NumPy, Pandas, Matplotlib, and Seaborn for data analysis\u003c\/li\u003e\n\u003cli\u003eApply linear algebra, calculus, probability, and statistics to ML\u003c\/li\u003e\n\u003cli\u003eBuild regression, classification, and k-NN models\u003c\/li\u003e\n\u003cli\u003eEngineer features and evaluate models with cross-validation and hyperparameter tuning\u003c\/li\u003e\n\u003cli\u003eTrain ensembles with random forests, XGBoost, LightGBM, and CatBoost\u003c\/li\u003e\n\u003cli\u003eBuild neural networks and CNNs with TensorFlow, Keras, and PyTorch\u003c\/li\u003e\n\u003cli\u003eDevelop RNNs, LSTMs, GRUs, attention, BERT, and GPT workflows for NLP\u003c\/li\u003e\n\u003cli\u003eApply transfer learning and fine-tuning to computer vision and NLP\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4\u003eWho this book is for\u003c\/h4\u003eThis book is for aspiring data scientists, machine learning engineers, AI developers, students, and career changers who want one structured path from Python fundamentals to machine learning and deep learning. It suits readers seeking practical skills in data analysis, predictive modeling, computer vision, NLP, transformers, and transfer learning. No prior machine learning or deep learning experience is required. Python is introduced from the fundamentals, although basic programming familiarity and foundational mathematics will help.","brand":"ThinkEDU","offers":[{"title":"Default Title","offer_id":60814863499550,"sku":"9781808086748","price":39.99,"currency_code":"USD","in_stock":true}]}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0800\/4435\/9966\/collections\/1024_3d131c73-17c2-4ed3-b204-7ae617b7f39f.jpg?v=1792702478","url":"https:\/\/thinkedu.com\/collections\/stem-steam-ebooks\/training-focus-business.oembed","provider":"ThinkEDU","version":"1.0","type":"link"}