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Using the Pi Camera and a Raspberry Pi board, expand and replicate interesting machine learning (ML) experiments. This book provides a solid overview of ML and a myriad of underlying topics to further explore. Non-technical discussions temper complex technical explanations to make the hottest and most complex topic in the hobbyist world of computing understandable and approachable. Machine learning, also commonly referred to as deep learning (DL), is currently being integrated into a multitude of commercial products as well as widely being used in industrial, medical, and military applications. It is hard to find any modern human activity, which has not been "touched" by artificial intelligence (AI) applications. Building on the concepts first presented in Beginning Artificial Intelligence with the Raspberry Pi, you’ll go beyond simply understanding the concepts of AI into working with real machine learning experiments and applying practical deep learning concepts to experiments with the Pi board and computer vision. What you learn with Machine Learning with the Raspberry Pi can then be moved on to other platforms to go even further in the world of AI and ML to better your hobbyist or commercial projects. What You'll Learn Acquire a working knowledge of current ML Use the Raspberry Pi to implement ML techniques and algorithms Apply AI and ML tools and techniques to your own work projects and studies Who This Book Is For Engineers and scientists but also experienced makers and hobbyists. Motivated high school students who desire to learn about ML can benefit from this material with determination.
Learn how to teach a Single Board Computer like a Raspberry Pi to recognize individual faces, using the latest Machine Learning techniques.
Machine Learning a branch of Artificial Intelligence is influencing the society, industry and academia at large. The adaptability of Python programming language to Machine Learning has increased its popularity further. Another technology on the horizon is Internet of Things (IoT). The present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer or have just started exploring IoT or Machine Learning with Python, then this book is for you. Features: Raspberry Pi as IoT is described along with the procedure for installation and configuration. A simple introduction to Python Programming Language along with its popular library packages like NumPy, Pandas, SciPy and Matplotlib are dealt in an exhaustive manner along with relevant examples. Machine Learning along with Python Scikit-Learn library is explained to audience with an emphasis on supervised learning and classification. Image processing on IoT is introduced to the audience who love to apply Machine Learning algorithms to Images The book follows hands-on approach and provide a huge collection of Python programs.
Apply machine learning using the Internet of Things (IoT) in the agriculture, telecom, and energy domains with case studies. This book begins by covering how to set up the software and hardware components including the various sensors to implement the case studies in Python. The case study section starts with an examination of call drop with IoT in the telecoms industry, followed by a case study on energy audit and predictive maintenance for an industrial machine, and finally covers techniques to predict cash crop failure in agribusiness. The last section covers pitfalls to avoid while implementing machine learning and IoT in these domains. After reading this book, you will know how IoT and machine learning are used in the example domains and have practical case studies to use and extend. You will be able to create enterprise-scale applications using Raspberry Pi 3 B+ and Arduino Mega 2560 with Python. What You Will Learn Implement machine learning with IoT and solve problems in the telecom, agriculture, and energy sectors with Python Set up and use industrial-grade IoT products, such as Modbus RS485 protocol devices, in practical scenarios Develop solutions for commercial-grade IoT or IIoT projects Implement case studies in machine learning with IoT from scratch Who This Book Is For Raspberry Pi and Arduino enthusiasts and data science and machine learning professionals.
"Machine Learning a branch of Artificial Intelligence is influencing the society, industry and academia at large. The adaptability of Python programming language to Machine Learning has increased its popularity further. Another technology on the horizon is the Internet of Things (IoT). The present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer or have just started exploring IoT or Machine Learning with Python, then this book is for you"--
Gain a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform. Most of the major AI topics will be explored, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more! AI in action will be demonstrated using the Python language on the Raspberry Pi. The Prolog language will also be introduced and used to demonstrate fundamental AI concepts. In addition, the Wolfram language will be used as part of the deep machine learning demonstrations. A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. Minimal expense is needed for the projects as only a few sensors and actuators will be required. Beginners and hobbyists can jump right in to creating AI projects with the Raspberry PI using this book. What You'll Learn What AI is and—as importantly—what it is not Inference and expert systems Machine learning both shallow and deep Fuzzy logic and how to apply to an actual control system When AI might be appropriate to include in a system Constraints and limitations of the Raspberry Pi AI implementation Who This Book Is For Hobbyists, makers, engineers involved in designing autonomous systems and wanting to gain an education in fundamental AI concepts, and non-technical readers who want to understand what AI is and how it might affect their lives.
Python Machine Learning Would you want to learn how to utilize Python to produce machine learning models, but you think it would be too complicated for you? Or maybe you like to automate simple stuff with your PC, but you do not know how to do it. As a novice, you might think programming is complicated. Understanding artificial intelligence coding could take several months. Not to mention that the chance of giving up before perfecting it could be high. Therefore, you could think of employing a professional developer to shorten the time if you have time to develop. That might look like a great solution, but it is surely very costly. You still have pay for the developer if he doesn't do the proper job you want. You know the best solution for this? The perfect solution is to follow a complete programming manual with hands-on projects as well as practical exercises. This book is structured as a course with six chapters. Inside the book, you will be able to go through a first section in which basic and fundamental notions of deep learning are mention, to get to the next chapters made to help you learn advanced coding insights needed to build training data sets for the development of successful machine learning models. In detail, you will learn: The Fundamentals of Machine Learning Machine-Learning Systems An Overview of Python for Machine Learning Understanding Python Libraries for Machine Learning Introducing Neural Networks and Deep Learning Practical Data Management What makes this book different? The majority of books available on the market take a brief look into machine learning, presenting some of the subjects but never going deep. This book is not one of those. Even if you are totally new to programming in 2020 or you're simply looking to widen your abilities as a programmer, this book is perfect for you! Well, stress no more! Buy this book and also learn all... and DOWNLOAD IT NOW!
Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users
If you have a passion for technology and want to explore the world of Raspberry Pi, then this book provides you with all the tools and information you are looking for. Although being familiar with basic programming concepts is useful, you can still learn a lot from this book as a wide variety of topics are covered.
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. This fun, DIY project book teaches computer vision technology using Raspberry Pi and Raspi-Cam Written by dedicated hobbyist and bestselling author Donald Norris, this guide provides an introduction to the emerging field of computer vision technology and features interesting projects that use cutting-edge, real-time imaging triggers. You will explore the basics of computer vision and get complete explanations of how to employ open-source software and inexpensive hardware, including Raspberry Pi, OpenCV, and the Raspberry Pi Camera Module. Computer Vision Using the Raspberry Pi for the Evil Genius discusses many different types of real-time visual triggers, including facial and low-light recognition, with easy-to-follow explanations of the systems that control them. The book then presents step-by-step, DIY home projects—from a pet gate that opens for your pet but can keep out all unwanted critters to an outdoor bird feeder that can count the number of bird visitors and record information on their species. There is also a project that shows how to conduct crowd size estimations. •Teaches the basics of computer vision technology using Raspberry Pi, OpenCV, and the Raspberry Pi Camera Module•Each project includes a parts list, illustrations, and easy-to-follow assembly instructions•Introduces computer vision using Keras, an open-source Python framework
This book is an easy-to-follow guide with practical examples in each chapter. Suitable for the novice and expert alike, each topic provides a fast and easy way to get started with exciting applications and also guides you through setting up the Raspberry Pi as a secret agent toolbox.
Start solving world issues by beginning small with simple Rasperry Pi projects. Using a free IoT server; tackle fundamental topics and concepts behind the Internet of Things. Image processing and sensor topics aren’t only applicable to the Raspberry Pi. The skills learned in this book can go own to other applications in mobile development and electrical engineering. Start by creating a system to detect movement through the use of a PIR motion sensor and a Raspberry Pi board. Then further your sensor systems by detecting more than simple motion. Use the MQ2 gas sensor and a Raspberry Pi board as a gas leak alarm system to detect dangerous explosive and fire hazards. Train your system to send the captured data to the remote server ThingSpeak. When a gas increase is detected beyond a limit, then a message is sent to your Twitter account. Having started with ThingSpeak, we’ll go on to develop a weather station with your Raspberry Pi. Using the DHT11 (humidity and temperature sensor) and BMP085 (barometric pressure and temperature sensor) in conjunction with ThingSpeak and Twitter, you can receive realtime weather alerts from your own meterological system! Finally, expand your skills into the popular machine learning world of digital image processing using OpenCV and a Pi. Make your own object classifiers and finally manipulate an object by means of an image in movement. This skillset has many applications, ranging from recognizing people or objects, to creating your own video surveillance system. With the skills developed in this book, you will have everything you need to work in IoT projects for the Pi. You can then expand your skills out further to develop mobile projects and delve into interactive systems such as those found in machine learning. What You'll Learn Work with ThingSpeak to receive Twitter alerts from your systems Cultivate skills in processing sensor inputs that are applicable to mobile and machine learning projects as well Incorporate sensors into projects to make devices that interact with more than just code Who This Book Is ForHobbyists and makers working robotics and Internet of Things areas will find this book a great resource for quick but expandable projects. Electronics engineers and programmers who would like to expand their familiarity with basic sensor projects will also find this book helpful.
If you are looking for a low budget, small form-factor remotely accessible hacking tool, then the concepts in this book are ideal for you. If you are a penetration tester who wants to save on travel costs by placing a low-cost node on a target network, you will save thousands by using the methods covered in this book. You do not have to be a skilled hacker or programmer to use this book. It will be beneficial to have some networking experience; however, it is not required to follow the concepts covered in this book.
This book is intended for developers who have worked with the Raspberry Pi and who want to learn how to make the most of the Raspbian operating system and their Raspberry Pi. Whether you are a beginner to the Raspberry Pi or a seasoned expert, this book will make you familiar with the Raspbian operating system and teach you how to get your Raspberry Pi up and running.
Machine Learning for Beginners Are you ready to spin up a virtual GPU instance and crash through petabytes of data? Do you like to add machine learning to your professional profile? But wait a minute. Before you go onboard on your grand expedition into the realm of machine learning, there's some theory you need to deal with first. Instead of wasting your money on a dense, boring, and lengthy textbook, you might like to read this book first. A concise and clear option to a textbook. Machine Learning for Beginners provides a high-level and efficient introduction to the basic components as well as statistical concepts seen in machine learning. This book has been written and created for absolute newbies like you. That means there won't be any jargon, plain English discussions, and no experience needed. Clear explanations are distributed throughout the book, making it engaging and simple for you to follow along at home, where core algorithms are presented. The book opens with a basic introduction to machine learning. The second half of the book is much practical and dives into specific algorithms and statistical concepts applied in machine learning. At the end of this book, the author share advice and insights on where machine learning will be in the next twenty years. In this book, you will learn about: Machine Learning Coding with Python Working with Raspberry Pi Working with TensorFlow Advanced Machine Learning Are you now thinking that there's no scientific or certainty proof that intelligence is ass structured as you hope it to be? As in the evolutionary processes, where order and chaos coexist, you will see a research gap connected to your mind and brain, normally related to concentrating on the model based on the order. Do you really like to learn more about machine learning? Then this book is the perfect solution for you. Well, stress no more! Buy this book and also learn all... and DOWNLOAD IT NOW!
Perform a wide variety of computer vision tasks such as image processing and manipulation, feature and object detection, and image restoration to build real-life computer vision applications Key Features Explore the potential of computer vision with Raspberry Pi and Python programming Perform computer vision tasks such as image processing and manipulation using OpenCV and Raspberry Pi Discover easy-to-follow examples and screenshots to implement popular computer vision techniques and applications Book Description Raspberry Pi is one of the popular single-board computers of our generation. All the major image processing and computer vision algorithms and operations can be implemented easily with OpenCV on Raspberry Pi. This updated second edition is packed with cutting-edge examples and new topics, and covers the latest versions of key technologies such as Python 3, Raspberry Pi, and OpenCV. This book will equip you with the skills required to successfully design and implement your own OpenCV, Raspberry Pi, and Python-based computer vision projects. At the start, you'll learn the basics of Python 3, and the fundamentals of single-board computers and NumPy. Next, you'll discover how to install OpenCV 4 for Python 3 on Raspberry Pi, before covering major techniques and algorithms in image processing, manipulation, and computer vision. By working through the steps in each chapter, you'll understand essential OpenCV features. Later sections will take you through creating graphical user interface (GUI) apps with GPIO and OpenCV. You'll also learn to use the new computer vision library, Mahotas, to perform various image processing operations. Finally, you'll explore the Jupyter Notebook and how to set up a Windows computer and Ubuntu for computer vision. By the end of this book, you'll be able to confidently build and deploy computer vision apps. What you will learn Set up a Raspberry Pi for computer vision applications Perform basic image processing with libraries such as NumPy, Matplotlib, and OpenCV Demonstrate arithmetical, logical, and other operations on images Work with a USB webcam and the Raspberry Pi Camera Module Implement low-pass and high-pass filters and understand their applications in image processing Cover advanced techniques such as histogram equalization and morphological transformations Create GUI apps with Python 3 and OpenCV Perform machine learning with K-means clustering and image quantization Who this book is for This book is for beginners as well as experienced Raspberry Pi and Python 3 enthusiasts who are looking to explore the amazing world of computer vision. Working knowledge of the Python 3 programming language is assumed.
This book provides a platform to understand Internet of things with Raspberry Pi and the basic knowledge of the programming and interfacing of the devices and designed systems. It broadly covers introduction to Internet of Things and enabling technologies, interfacing with Raspberry Pi and Arduino and interfacing with Raspberry Pi GPIO. Internet of Things with Raspberry pi and Arduino is aimed at senior undergraduate, graduate students and professionals in electrical engineering, computer engineering including robotics.
This book shows you how to build real-time image processing systems all the way through to house automation. Find out how you can develop a system based on small 32-bit ARM processors that gives you complete control through voice commands. Real-time image processing systems are utilized in a wide variety of applications, such as in traffic monitoring systems, medical image processing, and biometric security systems. In Real-Time IoT Imaging with Deep Neural Networks, you will learn how to make use of the best DNN models to detect object in images using Java and a wrapper for OpenCV. Take a closer look at how Java scripting works on the Raspberry Pi while preparing your Visual Studio code for remote programming. You will also gain insights on image and video scripting. Author Nicolas Modrzyk shows you how to use the Rhasspy voice platform to add a powerful voice assistant and completely run and control your Raspberry Pi from your computer. To get your voice intents for house automation ready, you will explore how Java connects to the MQTT and handles parametrized Rhasspy voice commands. With your voice-controlled system ready for operation, you will be able to perform simple tasks such as detecting cats, people, and coffee pots in your selected environment. Privacy and freedom are essential, so priority is given to using open source software and an on-device voice environment where you have full control of your data and video streams. Your voice commands are your own—and just your own. With recent advancements in the Internet of Things and machine learning, cutting edge image processing systems provide complete process automation. This practical book teaches you to build such a system, giving you complete control with minimal effort. What You Will Learn: Show mastery by creating OpenCV filters Execute a YOLO DNN model for image detection Apply the best Java scripting on Raspberry Pi 4 Prepare your setup for real-time remote programming Use the Rhasspy voice platform for handling voice commands and enhancing your house automation setup Who This Book Is For:Engineers, and Hobbyists wanting to use their favorite JVM to run Object Detection and Networks on a Raspberry Pi
Explains how to leverage the revolutionary Raspberry Pi computer in order to learn the versatile Python programming language. Original.

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