Tinyml
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Tinyml
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Author : Pete Warden
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-12-16
Tinyml written by Pete Warden and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Computers categories.
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size
Introduction To Tinyml
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Author : Rohit Sharma
language : en
Publisher: AITS Inc
Release Date : 2022-07-20
Introduction To Tinyml written by Rohit Sharma and has been published by AITS Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-20 with Business & Economics categories.
This book is an effort by AI Technology & Systems to demystify the TinyML technology including market, applications, algorithms, tools and technology. the book dive deeper into the technology beyond common application and keep it light for the readers with varying background including students, hobbyists, managers, market researchers and developers. It starts with introduction to TinyML with benefits and scalability. It introduces no-code and low-code tinyML platform to develop production worthy solutions including audio wake word, visual wake word, American sign language and predictive maintenance. Last two chapters are devoted to sensor and hardware agnostic autoML and tinyML compiler technologies. More information at http://thetinymlbook.com/
Tinyml Iot Artificial Intelligence Of Things Part 1 Basics Of Machine Learning
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Author : Roberto Francavilla
language : en
Publisher: Roberto Francavilla
Release Date : 101-01-01
Tinyml Iot Artificial Intelligence Of Things Part 1 Basics Of Machine Learning written by Roberto Francavilla and has been published by Roberto Francavilla this book supported file pdf, txt, epub, kindle and other format this book has been release on 101-01-01 with Computers categories.
The first step towards your future in Artificial Intelligence applied to the world of the Internet of Things! I am excited to introduce you to "The Basics of Machine Learning", the first volume of a complete path dedicated to the Artificial Intelligence of Things. A work designed for those who start from scratch but dream of becoming the protagonist of the Fourth Industrial Revolution! In simple, clear and practical language, I will guide you through the fascinating world of Machine Learning and Deep Learning, the technologies that are transforming our present and that will dominate our future. What you will find in this book: ✨ The mathematical foundations essential to understand Machine Learning. ✨ How the machine learning process really works. ✨ How to build your first neural network from scratch. ✨ Techniques for solving regression problems and classifying images. ✨ Winning strategies to combat overfitting and improve model performance. ✨ Design of Convolutional Neural Network (CNN) for real Computer Vision applications. Not just theory: a lot of practice, right away! ✅ Concrete exercises on Google Colab and other free notebooks. ✅ Ready-to-use Python scripts. ✅ Detailed video tutorials for each practical project. ✅ Access to extra content and updates on my YouTube channel! With this course you are not just learning: you are building real skills, ready to be applied in innovative projects, in the world of work, or in your future startup! If you're passionate about the future, don't wait – start your Machine Learning journey today. Become an innovator! 📚 Download the book now and join the next generation of AI pioneers! 🧠 Important note: THE BOOK HAS BEEN TRANSLATED FROM ITALIAN INTO YOUR LANGUAGE USING ARTIFICIAL INTELLIGENCE. THERE MAY BE INACCURACIES, ESPECIALLY IN THE SOFTWARE CODE. That’s why at the end of each tutorial, you’ll find a link to download the correct code. Additionally, the book is sold at a very low price. I hope you’ll appreciate the gesture in publishing it — I’m sure you’ll find it very interesting. 📬 For any info or feedback: [email protected]
Tinyml For Edge Intelligence In Iot And Lpwan Networks
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Author : Bharat S Chaudhari
language : en
Publisher: Elsevier
Release Date : 2024-05-29
Tinyml For Edge Intelligence In Iot And Lpwan Networks written by Bharat S Chaudhari and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-29 with Computers categories.
Recently, Tiny Machine Learning (TinyML) has gained incredible importance due to its capabilities of creating lightweight machine learning (ML) frameworks aiming at low latency, lower energy consumption, lower bandwidth requirement, improved data security and privacy, and other performance necessities. As billions of battery-operated embedded IoT and low power wide area networks (LPWAN) nodes with very low on-board memory and computational capabilities are getting connected to the Internet each year, there is a critical need to have a special computational framework like TinyML. TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to IoT and LPWANs. It starts by providing the foundations of IoT/LPWANs, low power embedded systems and hardware, the role of artificial intelligence and machine learning in communication networks in general and cloud/edge intelligence. It then presents the concepts, methods, algorithms and tools of TinyML. Practical applications of the use of TinyML are given from health and industrial fields which provide practical guidance on the design of applications and the selection of appropriate technologies. TinyML for Edge Intelligence in IoT and LPWAN Networks is highly suitable for academic researchers and professional system engineers, architects, designers, testers, deployment engineers seeking to design ultra-lower power and time-critical applications. It would also help in designing the networks for emerging and future applications for resource-constrained nodes. - This book provides one-stop solutions for emerging TinyML for IoT and LPWAN applications. - The principles and methods of TinyML are explained, with a focus on how it can be used for IoT, LPWANs, and 5G applications. - Applications from the healthcare and industrial sectors are presented. - Guidance on the design of applications and the selection of appropriate technologies is provided.
Tinyml Cookbook
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Author : Gian Marco Iodice
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-04-01
Tinyml Cookbook written by Gian Marco Iodice and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-01 with Computers categories.
Work through over 50 recipes to develop smart applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico using the power of machine learning Key Features Train and deploy ML models on Arduino Nano 33 BLE Sense and Raspberry Pi Pico Work with different ML frameworks such as TensorFlow Lite for Microcontrollers and Edge Impulse Explore cutting-edge technologies such as microTVM and Arm Ethos-U55 microNPU Book DescriptionThis book explores TinyML, a fast-growing field at the unique intersection of machine learning and embedded systems to make AI ubiquitous with extremely low-powered devices such as microcontrollers. The TinyML Cookbook starts with a practical introduction to this multidisciplinary field to get you up to speed with some of the fundamentals for deploying intelligent applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico. As you progress, you’ll tackle various problems that you may encounter while prototyping microcontrollers, such as controlling the LED state with GPIO and a push-button, supplying power to microcontrollers with batteries, and more. Next, you’ll cover recipes relating to temperature, humidity, and the three “V” sensors (Voice, Vision, and Vibration) to gain the necessary skills to implement end-to-end smart applications in different scenarios. Later, you’ll learn best practices for building tiny models for memory-constrained microcontrollers. Finally, you’ll explore two of the most recent technologies, microTVM and microNPU that will help you step up your TinyML game. By the end of this book, you’ll be well-versed with best practices and machine learning frameworks to develop ML apps easily on microcontrollers and have a clear understanding of the key aspects to consider during the development phase.What you will learn Understand the relevant microcontroller programming fundamentals Work with real-world sensors such as the microphone, camera, and accelerometer Run on-device machine learning with TensorFlow Lite for Microcontrollers Implement an app that responds to human voice with Edge Impulse Leverage transfer learning to classify indoor rooms with Arduino Nano 33 BLE Sense Create a gesture-recognition app with Raspberry Pi Pico Design a CIFAR-10 model for memory-constrained microcontrollers Run an image classifier on a virtual Arm Ethos-U55 microNPU with microTVM Who this book is for This book is for machine learning developers/engineers interested in developing machine learning applications on microcontrollers through practical examples quickly. Basic familiarity with C/C++, the Python programming language, and the command-line interface (CLI) is required. However, no prior knowledge of microcontrollers is necessary.
Machine Learning On Commodity Tiny Devices
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Author : Song Guo
language : en
Publisher: CRC Press
Release Date : 2022-12-13
Machine Learning On Commodity Tiny Devices written by Song Guo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-13 with Computers categories.
This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. This book presents on-device learning techniques covering model-level neural network design, algorithm-level training optimization and hardware-level instruction acceleration. Analyzing the limitations of conventional in-cloud computing would reveal that on-device learning is a promising research direction to meet the requirements of edge intelligence applications. As to the cutting-edge research of TinyML, implementing a high-efficiency learning framework and enabling system-level acceleration is one of the most fundamental issues. This book presents a comprehensive discussion of the latest research progress and provides system-level insights on designing TinyML frameworks, including neural network design, training algorithm optimization and domain-specific hardware acceleration. It identifies the main challenges when deploying TinyML tasks in the real world and guides the researchers to deploy a reliable learning system. This book will be of interest to students and scholars in the field of edge intelligence, especially to those with sufficient professional Edge AI skills. It will also be an excellent guide for researchers to implement high-performance TinyML systems.
Practical Deep Learning For Cloud Mobile And Edge
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Author : Anirudh Koul
language : en
Publisher: O'Reilly Media
Release Date : 2019-10-14
Practical Deep Learning For Cloud Mobile And Edge written by Anirudh Koul and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-14 with Computers categories.
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
13th International Conference On Information Systems And Advanced Technologies Icisat 2023
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Author : Mohamed Ridda Laouar
language : en
Publisher: Springer Nature
Release Date : 2024-07-30
13th International Conference On Information Systems And Advanced Technologies Icisat 2023 written by Mohamed Ridda Laouar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-30 with Computers categories.
This book covers the Proceedings of the 13th International Conference on Information Systems and Advanced Technologies “ICISAT’2023.” One of the evocative and valuable dimensions of this conference is the way it brings together researchers, scientists, academics, and engineers in the field from different countries and enables discussions and debate of relevant issues, challenges, opportunities, and research findings. The ICISAT’2023 conference provided a forum for research and developments in the field of information systems and advanced technologies and new trends in developing information systems organizational aspects of their development and intelligent aspects of the final product. The aim of the ICISAT’2023 is to report progress and development of methodologies, technologies, planning and implementation, tools, and standards in information systems, technologies, and sciences. ICISAT’2023 aims at addressing issues related to the intelligent information, data science, and decision support system, from multidisciplinary perspectives and to discuss the research, teaching, and professional practice in the field. The book of ICISAT’2023 includes selected papers from the 13th International Conference on Information Systems and Advanced Technologies “ICISAT’2023,” organized during December 29–30, 2023. In this book, researchers, professional software, and systems engineers from around the world addressed intelligent information, data science, and decision support system for the conference. The ideas and practical solutions described in the book are the outcome of dedicated research by academics and practitioners aiming to advance theory and practice in this research domain. The list of topics is in all the areas of modern intelligent information systems and technologies such as neural networks, evolutionary computing, adaptive systems, pervasive system, ubiquitous system, E-learning and teaching, knowledge-based paradigms, learning paradigms, intelligent data analysis, intelligent decision making and support system, intelligent network security, web intelligence, deep learning, natural language processing, image processing, general machine learning, and unsupervised learning.
Intelligent Systems And Advanced Computing Sciences
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Author : Hani Hagras
language : en
Publisher: Springer Nature
Release Date : 2025-07-01
Intelligent Systems And Advanced Computing Sciences written by Hani Hagras and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Computers categories.
This book constitutes revised selected papers from the thoroughly refereed conference proceedings of the 4th International Conference on Intelligent Systems and Advanced Computing Sciences, ISACS 2023, which took place in Taza, Morocco, in October 26–27, 2023. The 30 full papers and 8 short papers presented in these proceedings were carefully reviewed and selected from 131 submissions. This conference focusing on all theoretical and practical aspects related to information technology and communications security.
Artificial Intelligence Applications And Innovations
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Author : Ilias Maglogiannis
language : en
Publisher: Springer Nature
Release Date : 2023-05-31
Artificial Intelligence Applications And Innovations written by Ilias Maglogiannis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-31 with Computers categories.
This two-volume set of IFIP-AICT 675 and 676 constitutes the refereed proceedings of the 19th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2023, held in León, Spain, during June 14–17, 2023. This event was held in hybrid mode. The 75 regular papers and 17 short papers presented in this two-volume set were carefully reviewed and selected from 185 submissions. The papers cover the following topics: Deep Learning (Reinforcement/Recurrent Gradient Boosting/Adversarial); Agents/Case Based Reasoning/Sentiment Analysis; Biomedical - Image Analysis; CNN - Convolutional Neural Networks YOLO CNN; Cyber Security/Anomaly Detection; Explainable AI/Social Impact of AI; Graph Neural Networks/Constraint Programming; IoT/Fuzzy Modeling/Augmented Reality; LEARNING (Active-AutoEncoders-Federated); Machine Learning; Natural Language; Optimization-Genetic Programming; Robotics; Spiking NN; and Text Mining /Transfer Learning.