{"product_id":"tinyml-for-beginners-a-practical-guide-to-edge-impulse-tensorflow-lite-micro-stm32cube-ai-build-real-tinyml-projects-and-solve-quantization-dep-9798278382409","title":"TinyML for Beginners: A Practical Guide to Edge Impulse, TensorFlow Lite Micro \u0026 STM32Cube.AI - Build Real TinyML Projects and Solve Quantization, Dep","description":"\u003cp\u003e • Author(s): Vihaan Kulkarni\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Embedded Computer Systems\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eTinyML for Beginners\u003c\/b\u003e is a modern, hands-on introduction to building real, production-grade machine-learning systems on microcontrollers. Designed for absolute beginners and fast-moving engineers, this book teaches you how to bring AI directly to the edge using low-power devices such as ESP32, Raspberry Pi Pico (RP2040), and STM32 microcontrollers-without relying on cloud servers or expensive hardware.\u003c\/p\u003e\u003cp\u003eThis practical guide walks you step by step through the complete TinyML workflow: collecting sensor data, building optimized models, quantizing them for microcontroller limits, deploying them through TensorFlow Lite Micro, Edge Impulse, and STM32Cube.AI, and integrating them into real-time smart home automations. Every chapter includes hands-on labs with measurable outcomes, deployable code examples, and clear implementation patterns used in real embedded AI systems.\u003c\/p\u003e\u003cp\u003eReaders learn how to design reliable on-device models for gesture recognition, keyword spotting, environmental prediction, and vibration-based anomaly detection. The book also provides proven solutions to common TinyML pain points such as quantization accuracy loss, tensor arena overflows, preprocessing drift, memory constraints, sensor noise, deployment crashes, and slow inference latency.\u003c\/p\u003e\u003cp\u003eYou will build and deploy a complete full-stack TinyML smart home system-featuring multiple AI-powered nodes communicating via Wi-Fi, BLE, or MQTT-and learn how to monitor performance, reduce power consumption, perform OTA updates, and validate models in real environments.\u003c\/p\u003e\u003cp\u003eWhether you are a beginner exploring edge AI for the first time or an engineer building low-power intelligent devices, this book provides a fast, clear, and practical blueprint for success with modern TinyML.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eLearn how to: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eBuild real TinyML models using Edge Impulse, TensorFlow Lite Micro, and STM32Cube.AI\u003c\/li\u003e\n\u003cli\u003eCollect, label, and preprocess audio, IMU, vibration, and environmental datasets\u003c\/li\u003e\n\u003cli\u003eTrain and optimize models using quantization, pruning, and CMSIS-NN acceleration\u003c\/li\u003e\n\u003cli\u003eDeploy ML inference loops on ESP32, RP2040, and STM32 microcontrollers\u003c\/li\u003e\n\u003cli\u003eIntegrate microcontroller-based AI with Wi-Fi, BLE, MQTT, Node-RED, and Home Assistant\u003c\/li\u003e\n\u003cli\u003eDebug accuracy loss, latency spikes, operator mismatches, and memory overflows\u003c\/li\u003e\n\u003cli\u003eProfile power consumption and design energy-efficient sensing loops\u003c\/li\u003e\n\u003cli\u003eBuild full smart home automations triggered by TinyML predictions\u003c\/li\u003e\n\u003cli\u003eImplement field testing, concept-drift handling, and model lifecycle updates\u003c\/li\u003e\n\u003cli\u003eDeploy production-ready firmware with stable sensor pipelines and OTA support\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cb\u003eWhat makes this TinyML book different?\u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e100% practical, hands-on, project-driven\u003c\/li\u003e\n\u003cli\u003eUses modern 2024-2025 toolchains, libraries, and hardware\u003c\/li\u003e\n\u003cli\u003eCovers real-world pain points and how to solve them reliably\u003c\/li\u003e\n\u003cli\u003eIncludes chapter-based practice labs and a complete full-stack capstone project\u003c\/li\u003e\n\u003cli\u003eWritten to be beginner-friendly but technically accurate, complete, and professional\u003c\/li\u003e\n\u003cli\u003eFully aligned with how TinyML is deployed today in smart homes, IoT, wearables, and embedded systems\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eIf you want the fastest, clearest path to building real on-device AI systems-with modern tools, optimized models, reliable deployments, and practical smart home projects-this book is the perfect starting point.\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47593420292247,"sku":"9798278382409","price":2508.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798278382409.webp?v=1774981812","url":"https:\/\/atlanticbooks.com\/products\/tinyml-for-beginners-a-practical-guide-to-edge-impulse-tensorflow-lite-micro-stm32cube-ai-build-real-tinyml-projects-and-solve-quantization-dep-9798278382409","provider":"Atlantic Books","version":"1.0","type":"link"}