BASICS OF ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

BASICS OF ARTIFICIAL INTELLIGENCE & MACHINE LEARNING PDF Author: Dr Dheeraj Mehrotra
Publisher: Notion Press
ISBN: 1645872831
Category : Computers
Languages : en
Pages : 77

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Book Description
The concept of Artificial Intelligence (AI) & Machine Learning (ML) has been in practice for over years with the advent of technological progress. Over time, it has blended our lives through nearly every narration of learning, teaching, enjoyment, normal routine operations and what not. The aspect delivers a common understanding of the topics with reference to it making an impact on our lives, with a better framework of technology affecting our lives in particular. Let us look up to science for a change to be brought about in us. Let us create awareness of making technology available to people, in a broader sense. As that happens, people who are responsible need to be told about the use and misuse of the same. As we lead our lives, we come across the fact that AI, Robotics and Learning Machines seem to be the household topic of discussion. Earlier, AI was perceived to be reserved for only ‘Geniuses’ or ‘Researchers’ or the ‘computer’ community, but it very aptly integrates and impacts each and every aspect of our lives. Knowingly or unknowingly, it has become intellectually influential in shaping our thoughts, actions and the day-to-day chores.

Artificial Intelligence and Machine Learning Fundamentals

Artificial Intelligence and Machine Learning Fundamentals PDF Author: Zsolt Nagy
Publisher: Packt Publishing Ltd
ISBN: 1789809207
Category : Computers
Languages : en
Pages : 330

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Book Description
Create AI applications in Python and lay the foundations for your career in data science Key FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail with interesting examplesMaster core AI concepts with engaging activitiesBook Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! What you will learnUnderstand the importance, principles, and fields of AIImplement basic artificial intelligence concepts with PythonApply regression and classification concepts to real-world problemsPerform predictive analysis using decision trees and random forestsCarry out clustering using the k-means and mean shift algorithmsUnderstand the fundamentals of deep learning via practical examplesWho this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).

Artificial Intelligence Basics

Artificial Intelligence Basics PDF Author: Tom Taulli
Publisher: Apress
ISBN: 1484250281
Category : Computers
Languages : en
Pages : 195

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Book Description
Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. Author Tom Taulli provides an engaging, non-technical introduction to important concepts such as machine learning, deep learning, natural language processing (NLP), robotics, and more. In addition to guiding you through real-world case studies and practical implementation steps, Taulli uses his expertise to expand on the bigger questions that surround AI. These include societal trends, ethics, and future impact AI will have on world governments, company structures, and daily life. Google, Amazon, Facebook, and similar tech giants are far from the only organizations on which artificial intelligence has had—and will continue to have—an incredibly significant result. AI is the present and the future of your business as well as your home life. Strengthening your prowess on the subject will prove invaluable to your preparation for the future of tech, and Artificial Intelligence Basics is the indispensable guide that you’ve been seeking. What You Will Learn Study the core principles for AI approaches such as machine learning, deep learning, and NLP (Natural Language Processing)Discover the best practices to successfully implement AI by examining case studies including Uber, Facebook, Waymo, UiPath, and Stitch FixUnderstand how AI capabilities for robots can improve businessDeploy chatbots and Robotic Processing Automation (RPA) to save costs and improve customer serviceAvoid costly gotchasRecognize ethical concerns and other risk factors of using artificial intelligenceExamine the secular trends and how they may impact your business Who This Book Is For Readers without a technical background, such as managers, looking to understand AI to evaluate solutions.

Artificial Intelligence Basics

Artificial Intelligence Basics PDF Author: N. Gupta
Publisher: Mercury Learning and Information
ISBN: 1683925157
Category : Computers
Languages : en
Pages : 332

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Book Description
Designed as a self-teaching introduction to the fundamental concepts of artificial intelligence, the book begins with its history, the Turing test, and early applications. Later chapters cover the basics of searching, game playing, and knowledge representation. Expert systems and machine learning are covered in detail, followed by separate programming chapters on Prolog and Python. The concluding chapter on artificial intelligence machines and robotics is comprehensive with numerous modern applications. Features: Covers an introduction to concepts related to AI, including searching processes, knowledge representation, machine learning, expert systems, programming, and robotics Includes separate chapters on Prolog and Python to introduce basic programming techniques in AI

Machine Learning and Artificial Intelligence

Machine Learning and Artificial Intelligence PDF Author: Ameet V Joshi
Publisher: Springer Nature
ISBN: 3030266222
Category : Technology & Engineering
Languages : en
Pages : 262

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Book Description
This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspects of static and dynamic ML techniques. The forth part describes the practical applications where presented techniques can be applied. The fifth part introduces the user to some of the implementation strategies for solving real life ML problems. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals. It makes minimal use of mathematics to make the topics more intuitive and accessible. Presents a full reference to artificial intelligence and machine learning techniques - in theory and application; Provides a guide to AI and ML with minimal use of mathematics to make the topics more intuitive and accessible; Connects all ML and AI techniques to applications and introduces implementations.

Machine Learning for Kids

Machine Learning for Kids PDF Author: Dale Lane
Publisher: No Starch Press
ISBN: 1718500572
Category : Computers
Languages : en
Pages : 290

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Book Description
A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+

Artificial Intelligence

Artificial Intelligence PDF Author: Tim D. Washington
Publisher: Independently Published
ISBN: 9781798191729
Category : Computers
Languages : en
Pages : 48

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Book Description
What is Artificial Intelligence? Artificial intelligence is a system that tends to simulate intelligent behaviors into computer-controlled machines or digital computers. Artificial Intelligence normally gives a machine the ability to carry out tasks usually associated with intelligent beings like us. Some of these tasks include translating languages, decision-making, visual perception, and speech recognition. In simple terms, artificial intelligence is the capability of any machine to mimic intelligent human behavior. Contrary to what many may think, Artificial intelligence is not a new field of study. In fact, it is older than most millennials reading this guide now. This may make you wonder when the concept of AI really started and from whence it came. As you will learn, machine learning is going to be a big deal in the world of technology. Those who would have started using it to unlock their data will greatly benefit from it even before people realize it exists. As a smart person, you should use this book to familiarize yourself with how machine learning works and then learn how to use it to your advantage. These days, AI is associated with the high-tech companies that dominate the field. Artificial intelligence first started as an academic discipline, but it has since sunken its tendrils into the business sector. Many AI researchers have abandoned academia altogether and flocked to companies like Facebook, Microsoft, Alphabet (Google) Amazon, openAI, and so on. The said companies are all working on different machine learning algorithms and are without a doubt at the forefront of AI research. Those with advanced degrees in AI, computer science, and maths rather join the engineering teams of these companies than stay in the academia. And since they are at the bleeding edge, it is worth listening to what their leaders have to say. Some have been quiet on the concerns about AI, and others like Amazon's Bezos have said that they aren't worried about potential AI threats. But, other visionaries like Bill Gates, Elon Musk, and physicist Stephen Hawking have all voiced their opinions on the potential dangers of Artificial Intelligence. In January 2015, Hawking, Musk, and several other AI experts signed an open letter on artificial intelligence research, calling for increased study on the potential effects on society. The twelve-page document is entitled "Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter". It calls for further research on new AI legislation, privacy, ethics research, and several other concerns. As described in the letter, the potential threats of artificial intelligence can fall into multiple dimensions. The good news is that the early stages of AI development that we find ourselves in are malleable. The future is ours to create, provided that proper time and care go into the non-engineering side of AI research and policy. Book Outline: Chapter 1 - Artificial Beings, a Brief History of the Human Psyche Chapter 2 - Top Six AI Myths Chapter 3 - Why AI is the New Business Degree Chapter 4 - Understanding Machine Learning Chapter 5 - Machine Learning Steps Chapter 6 - Robotics Chapter 7 - Natural Language Processing

Mathematics for Machine Learning

Mathematics for Machine Learning PDF Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392

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Book Description
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Artificial Intelligence with Python

Artificial Intelligence with Python PDF Author: Prateek Joshi
Publisher: Packt Publishing Ltd
ISBN: 1786469677
Category : Computers
Languages : en
Pages : 437

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Book Description
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.

Artificial Intelligence: The Basics

Artificial Intelligence: The Basics PDF Author: Kevin Warwick
Publisher: Routledge
ISBN: 1136629831
Category : Philosophy
Languages : en
Pages : 192

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Book Description
'if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory input in machine systems the nature of consciousness the controversial culturing of human neurons. Exploring issues at the heart of the subject, this book is suitable for anyone interested in AI, and provides an illuminating and accessible introduction to this fascinating subject.