Ai Iot And Machine Learning Basics
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AI, IOT and Machine Learning Basics
Author: Aashish Mishra
language: en
Publisher: Shodh sagar international publication
Release Date: 2025-05-28
AI, IoT and Machine Learning Basics is a concise, beginner-friendly guide that demystifies the core technologies shaping the future. Whether you're a student, tech enthusiast, or a professional seeking to understand the digital transformation landscape, this book offers clear explanations and practical insights into three of today's most disruptive technologies: Artificial Intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML). Inside, you'll learn: What AI, IoT, and ML really mean — and how they’re different Real-world applications across industries Key concepts, tools, and terminology made easy The ethical and societal implications of intelligent systems How these technologies work together to power smart solutions Perfect for non-technical readers and those new to the field, this book provides a solid foundation to begin exploring more advanced topics. If you're curious about the tech revolution and want a clear, jargon-free introduction, this is the book for you.
AI, IOT AND MACHINE LEARNING BASICS
Author: Dr Aadam Quraishi MD
language: en
Publisher: Xoffencer intrernational book publication house
Release Date: 2024-12-30
The 21st century has ushered in a period of unparalleled technological developments, which have radically altered how we live, work, and interact with the environment that surrounds us. Artificial Intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) are three revolutionary technologies that are at the heart of this massive upheaval. These technologies are no longer something that will be developed in the future; rather, they are now influencing industries, spurring innovation, and building systems that are smarter and more connected. Since the advent of the digital revolution, the gap between the physical and virtual realities has been crossed. This has made it possible for computers to carry out activities, make judgments, and learn from data with minimum assistance from humans. The Internet of Things (IoT) links common devices to the Internet, artificial intelligence (AI) enables systems to imitate human intellect, and machine learning (ML) enables computers to learn from huge quantities of data to make predictions and improve performance over time. In a society that is becoming more and more dependent on intelligent solutions, understanding these technologies is no longer an option. Artificial intelligence (AI), the Internet of Things (IoT), and machine learning have permeated every facet of contemporary life, from wearable gadgets and smart homes to predictive healthcare and driverless automobiles. What drives me: As will be explained in the chapter, the AI/ML-based Internet of Things systems are making significant contributions to the advancement of all areas of technology and society. As a result, gaining knowledge about these systems, even if it is in a general sense, would be beneficial to our growth even in our specialized areas. Because it has demonstrated its usefulness across all sectors and businesses, the potential that this technological combination possesses is not something that one can either ignore or choose to ignore. It will undoubtedly transform from a talent that can be added to one that is required in the future. In this chapter, you will get an understanding of the most popular 2 | P a g e terminology in the world of technology today, including artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT), as well as how these concepts interact with one another. In this course, you will learn about the rapidly expanding field of artificial intelligence-based Internet of Things (IoT) technologies and how these systems are utilized in everyday life to simplify our lives and enrich our experiences. Your perspective will broaden as a result of the numerous applications that will be discussed, particularly about how this technology may be utilized and how you can benefit from it. 1.2 ARTIFICIAL INTELLIGENCE We all now have a general understanding of artificial intelligence and how it works. To summarise the information that was presented in the introduction, artificial intelligence (AI) can be defined as "a vast branch of computer science that endeavors to build smart entities capable of performing intelligent tasks without human intervention." In other words, AI is the simulation of human intelligence in machines, which grants them the capabilities to mimic and behave like humans. These entities are grouped under a single umbrella term known as Intelligent Agents (IA). If an entity can see its surroundings, comprehend it, and act upon it, then that creature is considered an IA. It is possible to perceive it as being composed of three halves. First, there are the Sensors in the system. It is a reference to the portion of the AI that is responsible for assisting it in perceiving stimuli from the outside environment. The Actuators are the second entity in the system. AI can include methods that create the required effects with the assistance of this. The third component of the agent is the Effector, which is utilized by the agent to exert its influence on the surrounding environment. Consequently, we can comprehend the idea of PEAS from this. Performance Measurement, Environment, Actuator, and Sensor are the components that make up PEAS. Using PEAS, we can gain a more in-depth understanding of Intelligent Agents, which in turn helps us develop more effective Rational Agents. A performance metric is a judgment of how well something is performing. Environment is a term that relates to the surrounding environment, which includes the entities that are doing the act. Actuators are the components or instruments that are essential to the operation of the mechanism
Artificial Intelligence for IoT Cookbook
Author: Michael Roshak
language: en
Publisher: Packt Publishing Ltd
Release Date: 2021-03-05
Implement machine learning and deep learning techniques to perform predictive analytics on real-time IoT data Key FeaturesDiscover quick solutions to common problems that you'll face while building smart IoT applicationsImplement advanced techniques such as computer vision, NLP, and embedded machine learningBuild, maintain, and deploy machine learning systems to extract key insights from IoT dataBook Description Artificial intelligence (AI) is rapidly finding practical applications across a wide variety of industry verticals, and the Internet of Things (IoT) is one of them. Developers are looking for ways to make IoT devices smarter and to make users' lives easier. With this AI cookbook, you'll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions, along with covering advanced AI techniques that facilitate analytics and learning in various IoT applications. Using a recipe-based approach, the book will take you through essential processes such as data collection, data analysis, modeling, statistics and monitoring, and deployment. You'll use real-life datasets from smart homes, industrial IoT, and smart devices to train and evaluate simple to complex models and make predictions using trained models. Later chapters will take you through the key challenges faced while implementing machine learning, deep learning, and other AI techniques, such as natural language processing (NLP), computer vision, and embedded machine learning for building smart IoT systems. In addition to this, you'll learn how to deploy models and improve their performance with ease. By the end of this book, you'll be able to package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems. What you will learnExplore various AI techniques to build smart IoT solutions from scratchUse machine learning and deep learning techniques to build smart voice recognition and facial detection systemsGain insights into IoT data using algorithms and implement them in projectsPerform anomaly detection for time series data and other types of IoT dataImplement embedded systems learning techniques for machine learning on small devicesApply pre-trained machine learning models to an edge deviceDeploy machine learning models to web apps and mobile using TensorFlow.js and JavaWho this book is for If you're an IoT practitioner looking to incorporate AI techniques to build smart IoT solutions without having to trawl through a lot of AI theory, this AI IoT book is for you. Data scientists and AI developers who want to build IoT-focused AI solutions will also find this book useful. Knowledge of the Python programming language and basic IoT concepts is required to grasp the concepts covered in this artificial intelligence book more effectively.