{"product_id":"edge-ai-for-iot-devices-thom-haagenrud-9798247194415","title":"Edge AI for IoT Devices: Run models efficiently on microcontrollers","description":"\u003cb\u003eBig AI. Tiny Hardware.\u003c\/b\u003e\u003cp\u003e\u003cb\u003eThe cloud is too slow. The cloud is too expensive. It's time to put the brain directly on the chip.\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eFor years, \"Artificial Intelligence\" meant massive GPUs and server farms. But the next revolution isn't happening in a data center-it's happening on a microcontroller smaller than your thumbnail. \u003ci\u003eEdge AI for IoT Devices\u003c\/i\u003e is the definitive guide to \u003cb\u003eTinyML\u003c\/b\u003e: the art of running machine learning models on constrained hardware with kilobytes of memory, not gigabytes.\u003c\/p\u003e\u003cp\u003eThis book is for the embedded engineer who wants to add intelligence to their products without adding cost, and for the data scientist who wants to deploy their models to the physical edge. You will learn to squeeze neural networks onto devices like the ESP32, Arduino Nano 33 BLE, and STM32, enabling them to see, hear, and feel in real-time.\u003c\/p\u003e\u003cb\u003eIntelligence, Unplugged.\u003c\/b\u003e\u003cp\u003eFrom \"Hey Google\" style voice recognition to industrial predictive maintenance, this guide covers the full workflow of embedded machine learning.\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003e\u003cb\u003eThe TinyML Workflow: \u003c\/b\u003e Learn the end-to-end process of collecting data, training a model in TensorFlow, and converting it to C++ for deployment on bare metal.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003e\u003cb\u003eExtreme Optimization: \u003c\/b\u003e Master \u003cb\u003eQuantization\u003c\/b\u003e (turning 32-bit floats into 8-bit integers) and \u003cb\u003ePruning\u003c\/b\u003e to make your models 90% smaller and faster without losing accuracy.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003e\u003cb\u003eSensor Intelligence: \u003c\/b\u003e Build projects that use accelerometers for gesture recognition and microphones for keyword spotting.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003e\u003cb\u003eAnomaly Detection: \u003c\/b\u003e Create systems that \"learn\" what normal vibration looks like on a motor and trigger an alert \u003ci\u003ebefore\u003c\/i\u003e the machine breaks-all locally.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003e\u003cb\u003eEnergy Management: \u003c\/b\u003e Techniques to duty-cycle your AI inference so your smart device can run for months on a coin cell battery.\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eWhether you are building a smart wearable, a remote wildlife camera, or an industrial sensor node, this book gives you the tools to sever the connection to the cloud.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eStop sending data. Start sending insights. Scroll up and get your copy to master the cutting edge of Edge AI.\u003c\/b\u003e\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Thom Haagenrud\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9798247194415\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Independently Published\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 02\/06\/2026\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 140\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.43lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.00h x 6.00w x 0.30d","brand":"Thom Haagenrud","offers":[{"title":"Paperback","offer_id":48517120098559,"sku":"9798247194415","price":16.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_8e11f6a6-335d-4867-bde7-6f42576f1667.jpg?v=1778730036","url":"https:\/\/www.whiterainbookhouse.com\/products\/edge-ai-for-iot-devices-thom-haagenrud-9798247194415","provider":"WR Book House","version":"1.0","type":"link"}