Download or read book Artificial Intelligence and Machine Learning Fundamentals written by Zsolt Nagy and published by Packt Publishing Ltd. This book was released on 2018-12-12 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).
Download or read book Fundamentals of Artificial Intelligence written by K.R. Chowdhary and published by Springer Nature. This book was released on 2020-04-04 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Artificial Intelligence introduces the foundations of present day AI and provides coverage to recent developments in AI such as Constraint Satisfaction Problems, Adversarial Search and Game Theory, Statistical Learning Theory, Automated Planning, Intelligent Agents, Information Retrieval, Natural Language & Speech Processing, and Machine Vision. The book features a wealth of examples and illustrations, and practical approaches along with the theoretical concepts. It covers all major areas of AI in the domain of recent developments. The book is intended primarily for students who major in computer science at undergraduate and graduate level but will also be of interest as a foundation to researchers in the area of AI.
Download or read book The Fundamentals Of Artificial Intelligence And Machine Learning written by Dr. N. Balajiraja and published by Academic Guru Publishing House. This book was released on 2023-11-22 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning and Artificial Intelligence are pillars on which you can build intelligent applications. This field is essential in the modern world since robots may now display complex cognitive abilities including as decision-making, learning and seeing the environment, behaviour prediction, and language processing. The terms "artificial intelligence" & "machine learning" are often used interchangeably, although they refer to two distinct processes. Machine learning is a branch of artificial intelligence that allows intelligent systems to autonomously learn new things from data, while artificial intelligence as a whole refers to robots that can make choices, acquire new skills, and solve problems. The engineering profession makes extensive use of AI methods to address a broad variety of previously intractable issues. The purpose of this book is to bring together developed form scientists, researchers, and academics to discuss all aspects of artificial intelligence and share their findings with one another and the wider scientific community. The book serves as a leading multidisciplinary forum for discussing real-world problems and the solutions that have been implemented to address them.
Download or read book Artificial Intelligence written by Tim D. Washington and published by Independently Published. This book was released on 2019-02-27 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Fundamentals of Deep Learning written by Nikhil Buduma and published by "O'Reilly Media, Inc.". This book was released on 2017-05-25 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning
Download or read book Fundamentals of Artificial Intelligence Machine Learning written by Dr. Shoieb Ahamed and published by Academic Guru Publishing House. This book was released on 2023-10-13 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: We have been curious in teaching computers to learn ever since they were first developed. The implications would be enormous if we knew how to teach them, via programming, to learn and improve automatically with use. Think of personal software assistants that learn their users’ changing interests and then highlight the stories from the online morning newspaper that are most relevant to them based on that information; computers that learn from medical records which treatments are best for new diseases; homes that learn to optimise energy costs based on the unique usage patterns of their occupants. If we could figure out how to teach machines, it would pave the way for all sorts of advanced computing applications and individualised experiences. Human learning skills (and shortcomings) may be better understood with a deeper knowledge of information processing methods for machine learning. Within the recent decade, “machine learning” and “artificial intelligence” have been widely used in a variety of settings. Both phrases are widely used in the scientific and media communities, often with overlapping but not always synonymous meanings. The authors of this book set out to define the terminologies at play here and, more specifically, to outline the role that machine learning plays in AI. The authors provide a literature analysis and a conceptual framework that explain how machine learning contributes to the development of (artificial) intelligent agents.
Download or read book Fundamentals of Machine Learning written by Thomas Trappenberg and published by Oxford University Press. This book was released on 2019-11-28 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in machine learning is exploding worldwide, both in research and for industrial applications. Machine learning is fast becoming a fundamental part of everyday life. This book is a brief introduction to this area - exploring its importance in a range of many disciplines, from science to engineering, and even its broader impact on our society. The book is written in a style that strikes a balance between brevity of explanation, rigorous mathematical argument, and outlines principle ideas. At the same time, it provides a comprehensive overview of a variety of methods and their application within this field. This includes an introduction to Bayesian approaches to modeling, as well as deep learning. Writing small programs to apply machine learning techniques is made easy by high level programming systems, and this book shows examples in Python with the machine learning libraries 'sklearn' and 'Keras'. The first four chapters concentrate on the practical side of applying machine learning techniques. The following four chapters discuss more fundamental concepts that includes their formulation in a probabilistic context. This is followed by two more chapters on advanced models, that of recurrent neural networks and that of reinforcement learning. The book closes with a brief discussion on the impact of machine learning and AI on our society. Fundamentals of Machine Learning provides a brief and accessible introduction to this rapidly growing field, one that will appeal to students and researchers across computer science and computational neuroscience, as well as the broader cognitive sciences.
Download or read book Artificial Intelligence Fundamentals for Business Leaders written by I. Almeida and published by Now Next Later AI. This book was released on 2023-06 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2024 Edition. Free access to the AI Academy! The perfect guide to help non-technical business leaders understand the power of AI. Completely up to date with the latest advancements in generative AI. Part of the Byte-sized Learning AI series by Now Next Later AI, these books break down complex concepts into easily digestible pieces, providing you with a solid foundation in the fundamentals of AI. More Than a Book By purchasing this book, you will also be granted free access to the AI Academy platform. There you can view free course modules, test your knowledge through quizzes, attend webinars, and engage in discussion with other readers. You will also receive free modules and 50% discount toward the enrollment in the self-paced course of the same name and enjoy video summary lessons, instructor-graded assignments, and live sessions. A course certificate will be awarded upon successful completion. AI Academy by Now Next Later AI We are the most trusted and effective learning platform dedicated to empowering leaders with the knowledge and skills needed to harness the power of AI safely and ethically. Book and Course Learning Rubric - Chapters 1-7: Understanding of AI [11%] —Demonstrated comprehension of AI's evolution, definition, applications, and comparison with human intelligence. - Chapters 8-13: Understanding of Data and Data Management [11%] — Clear understanding of the significance of big data, and strategies for data management. - Chapters 14-29: Understanding of Machine Learning [30%] — Familiarity with machine learning algorithms, different learning types, and the key steps involved in a machine learning project. - Chapters 30-35: Understanding of Deep Learning [9%] — Understanding of deep learning, its basics, and the structure and types of neural networks. - Chapters 36-40: Understanding of Model Selection and Evaluation [9%] — Ability to select and evaluate machine learning models and utilize them for decision-making. - Chapters 41-50: Understanding of Generative AI [15%] — Detailed understanding of generative AI, its value chain, models, prompt strategies, applications, opportunities, and governance challenges. Assignment: Practical Application [15%] — Ability to apply generative AI understanding to real-world business challenges, demonstrating critical thinking and strategic planning skills.
Download or read book Artificial Intelligence and Machine Learning written by Lyla B. Das and published by I K International Pvt Ltd. This book was released on 2023-06-06 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed for undergraduates, postgraduates and professionals who want to have a firm grip on the fundamental principles of AI and ML. Artificial Intelligence (AI) is a broad area of knowledge which has percolated into every aspect of human life. ‘Machine Learning algorithms’ are considered to be a subset of AI Theory, mathematics and coding are three aspects to any topic in AI. This book covers the most relevant topics in the field of Artificial Intelligence and Machine Learning (ML). The subdivisions of Machine Learning are Supervised, Unsupervised and Reinforcement learning. All three are covered in sufficient depth. One very important and upcoming field of application is Natural Language Processing (NLP). A whole section of the book has been devoted to this. The book covers the conceptual, mathematical and numerical analysis of the important ML algorithms and their practical applications. The topics covered include AI search algorithms, Classical machine learning, Deep learning theory and popular networks, Natural Language Processing (NLP) and Reinforcement learning. Numerical examples and lucid explanations give the reader an easy entry into the world of AI and ML.
Download or read book Artificial Intelligence Basics written by Tom Taulli and published by Apress. This book was released on 2019-08-01 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book BASICS OF ARTIFICIAL INTELLIGENCE MACHINE LEARNING written by Dr Dheeraj Mehrotra and published by Notion Press. This book was released on 2019-06-03 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Artificial Intelligence and Machine Learning Fundamentals written by Zsolt Nagy and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Machine learning and neural networks are fast becoming pillars on which you can build intelligent applications. The course will begin by introducing you to Python and discussing using AI search algorithms. You will learn math-heavy topics, such as regression and classification, illustrated by Python examples. You will then progress on to advanced AI techniques and concepts, and work on real-life data sets to form decision trees and clusters. You will be introduced to neural networks, which is a powerful tool benefiting from Moore's law applied on 21st-century computing power. By the end of this course, you will feel confident and look forward to building your own AI applications with your newly-acquired skills!"--Resource description page.
Download or read book Machine Learning and Data Science written by Prateek Agrawal and published by John Wiley & Sons. This book was released on 2022-07-25 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: MACHINE LEARNING AND DATA SCIENCE Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia. Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms. These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.
Download or read book Artificial Intelligence and Machine Learning for Business written by Steven Finlay and published by Relativistic. This book was released on 2018-07 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) and Machine Learning are now mainstream business tools. They are being applied across many industries to increase profits, reduce costs, save lives and improve customer experiences. Organizations which understand these tools and know how to use them are benefiting at the expense of their rivals. Artificial Intelligence and Machine Learning for Business cuts through the hype and technical jargon that is often associated with these subjects. It delivers a simple and concise introduction for managers and business people. The focus is very much on practical application and how to work with technical specialists (data scientists) to maximize the benefits of these technologies. This third edition has been substantially revised and updated. It contains several new chapters and covers a broader set of topics than before, but retains the no-nonsense style of the original.
Download or read book Machine Learning written by Oliver Tensor and published by Charlie Creative Lab Limited Publisher. This book was released on 2021-01-20 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get this book with 55% discount !! Do you want to learn the progress made in the web marketing space and how you can exploit it for your marketing strategies? Do you want to gain an edge over your business's competitors?If you want to know How Machine Learning and Artificial Intelligence Technology can give your business a major performance boost, then keep reading. The Fourth Industrial Revolution is upon us, led by the Artificial Intelligence technology and setting the humankind for a global social transformation. The powerful applications of AI have already transformed our daily lives. Tools such as virtual personal and home assistants (like Siri in Apple Pods and Alexa in Amazon Echo) have become everyday usage products. Moreover, our digital lives have inundated organizations with astronomical volumes of data with hidden treasures of valuable insights. This information can be uncovered with the use of big data analytics and applied in combination with the Artificial Intelligence technology to increase your business performance efficiency. Learning to incorporate the Artificial Intelligence applications, Machine Learning, and Big Data Analytics in line with your company's domain can only give your business positive results. Machine Learning: The Definive Guide includes 3 books - Machine Learning for Beginners- Artificial Intelligence Business Applications- Artificial Intelligence and Machine Learning for Business Our aim with this book is to provide you a 360 view of the fundamentals and importance of Machine Learning and Artificial Intelligence Technology. You Will Learn: The Fundamentals of Artificial Intelligence and Machine Learning Applications, and Why are They so Important in the World Today. Gain an In-depth Understanding of 12 of the Most Popular Artificial Intelligence Tools in the Market, in an Easy to Understand and Colloquial Language. The Science of Big Data and How Companies are Increasingly Employing Good Analytical Tools to Makes Sense of an Estimated 1.7 MB of Data that will be Generated per Second per Person by 2020. What Different Types of Machine Learning Algorithms are and How They Work to Make Machines Able to Learn and Train themselves with Repeated Use. Even if you are a beginner, you will be armed to make sound personal and professional technological choices.
Download or read book Artificial Intelligence Basics written by N. Gupta and published by Mercury Learning and Information. This book was released on 2020-02-18 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Fundamentals of Reinforcement Learning written by Rafael Ris-Ala and published by Springer Nature. This book was released on 2023-08-14 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) applications bring agility and modernity to our lives, and the reinforcement learning technique is at the forefront of this technology. It can outperform human competitors in strategy games, creative compositing, and autonomous movement. Moreover, it is just starting to transform our civilization. This book provides an introduction to AI, specifies machine learning techniques, and explores various aspects of reinforcement learning, approaching the latest concepts in a didactic and illustrated manner. It is aimed at students who want to be part of technological advances and professors engaged in the development of innovative applications, helping with academic and industrial challenges. Understanding the Fundamentals of Reinforcement Learning will allow you to: Understand essential AI concepts Gain professional experience Interpret sequential decision problems and solve them with reinforcement learning Learn how the Q-Learning algorithm works Practice with commented Python code Find advantageous directions
