Artificial Intelligence Machine Learning And Deep Learning
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Ai Machine Learning And Deep Learning
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Author : Fei Hu
language : en
Publisher: CRC Press
Release Date : 2023-06-05
Ai Machine Learning And Deep Learning written by Fei Hu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-05 with Computers categories.
Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models and algorithms can actually also be used for cyber security (i.e., the use of AI to achieve security). Since AI/ML/DL security is a newly emergent field, many researchers and industry professionals cannot yet obtain a detailed, comprehensive understanding of this area. This book aims to provide a complete picture of the challenges and solutions to related security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then, the book describes many sets of promising solutions to achieve AI security and privacy. The features of this book have seven aspects: This is the first book to explain various practical attacks and countermeasures to AI systems Both quantitative math models and practical security implementations are provided It covers both "securing the AI system itself" and "using AI to achieve security" It covers all the advanced AI attacks and threats with detailed attack models It provides multiple solution spaces to the security and privacy issues in AI tools The differences among ML and DL security and privacy issues are explained Many practical security applications are covered
Artificial Intelligence Machine Learning And Deep Learning In Precision Medicine In Liver Diseases
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Author : Tung-Hung Su
language : en
Publisher: Elsevier
Release Date : 2023-08-20
Artificial Intelligence Machine Learning And Deep Learning In Precision Medicine In Liver Diseases written by Tung-Hung Su and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-20 with Science categories.
Artificial Intelligence, Machine Learning, and Deep Learning in Precision Medicine and Liver Diseases: Concept, Technology, Application, and Perspectives combines four major applications of artificial intelligence (AI) within the field of clinical medicine specific to liver diseases: radiology imaging, electronic health records, pathology, and multiomics. The book provides a state-of-the-art summary of AI in precision medicine in hepatology, clarifying the concept and technology of AI and pointing to the current and future applications of AI within the field of hepatology. Coverage includes data preparation, methodology and application within disease-specific cases in fibrosis, viral and steatohepatitis, cirrhosis, hepatocellular carcinoma, acute liver failure, liver transplantation, and more. The ethical and legal issues of AI and future challenges and perspectives are also discussed. By highlighting many new AI applications which can further research, diagnosis, and treatment, this reference is the perfect resource for both practicing hepatologists and researchers focused on AI applications in medicine. - Introduces the concept of AI and machine learning of precision medicine in the field of hepatology - Discusses current challenges of AI in healthcare and proposes future tasks for AI in new workflows of healthcare - Provides real-world applications from domain experts in clinical medicine
The Ultimate Modern Guide To Artificial Intelligence
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Author : Enamul Haque
language : en
Publisher: Enamul Haque
Release Date : 2020-07-21
The Ultimate Modern Guide To Artificial Intelligence written by Enamul Haque and has been published by Enamul Haque this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-21 with Computers categories.
The era of artificial intelligence has arrived. You, who only felt far from artificial intelligence, and the growing dream trees, are now inseparable from artificial intelligence. What does AI have to do with me? Isn't it a distant future that has nothing to do with me, not a scientist, a technician, or a computer programmer? Well, Artificial intelligence is not a story of someone who has nothing to do with it, but the fact is, it is now everyone's story. AI is already deeply infiltrating everyone's life. The question is no longer whether we use technology or not; it's about working together in a better way. Surrounding technologies like Siri, Alexa, or Cortana are seamlessly integrated into our interactions. We walk into the room, turn on the lights, play songs, change the room temperature, keep track of shopping lists, book a ride at the airport, or remind ourselves to take the proper medication on time. It is now necessary to look at artificial intelligence from a broader and larger perspective. You should not just hang on to complex deep learning algorithms and think only through science and technology but through the eyes of emotions and humanities. These days, elementary school students learn English and coding at school. Tomorrow's elementary school students will learn AI. Of course, not everyone needs to be an AI expert. But if you don't understand AI, you will be left out of the trend of changing times. AI comes before English and coding. This is because artificial intelligence is the language and tool of the future. This book opens your door to the most critical understanding needed of AI and other relevant disruptive technologies. Artificial intelligence will significantly change societal structures and the operations of companies. The next generation of employees needs to be trained as a workforce before entering the job market, and the existing workforce is regularly recharged and skilled. There is plenty on this for reskilling too. This is the most definitive compendium of AI, The Internet of Things, Machine Learning, Deep Learning, Data Science, Big Data, Cloud Computing, Neural networks, Robotics, the future of work and the future of intelligent industries.
Artificial Intelligence By Example
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Author : Denis Rothman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-31
Artificial Intelligence By Example written by Denis Rothman 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 2018-05-31 with Computers categories.
Be an adaptive thinker that leads the way to Artificial Intelligence Key Features AI-based examples to guide you in designing and implementing machine intelligence Develop your own method for future AI solutions Acquire advanced AI, machine learning, and deep learning design skills Book Description Artificial Intelligence has the potential to replicate humans in every field. This book serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies. Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks. You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own. By the end of this book, will have understood the fundamentals of AI and worked through a number of case studies that will help you develop business vision. What you will learn Use adaptive thinking to solve real-life AI case studies Rise beyond being a modern-day factory code worker Acquire advanced AI, machine learning, and deep learning designing skills Learn about cognitive NLP chatbots, quantum computing, and IoT and blockchain technology Understand future AI solutions and adapt quickly to them Develop out-of-the-box thinking to face any challenge the market presents Who this book is for Artificial Intelligence by Example is a simple, explanatory, and descriptive guide for junior developers, experienced developers, technology consultants, and those interested in AI who want to understand the fundamentals of Artificial Intelligence and implement it practically by devising smart solutions. Prior experience with Python and statistical knowledge is essential to make the most out of this book.
Artificial Intelligence Machine Learning And Deep Learning
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Author : Oswald Campesato
language : en
Publisher:
Release Date : 2020-01-30
Artificial Intelligence Machine Learning And Deep Learning written by Oswald Campesato and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-30 with Computers categories.
This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learningclassifiers such as logistic regression, k-NN, decision trees, random forests,and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs,LSTMs, and auto encoders. Keras-based code samples are included to supplementthe theoretical discussion. In addition, this book contains appendices forKeras, TensorFlow 2, and Pandas. Features: Covers an introduction toprogramming concepts related to AI, machine learning, and deep learning Includes material on Keras, TensorFlow2 and Pandas
Artificial Intelligence For Science A Deep Learning Revolution
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Author : Alok Choudhary
language : en
Publisher: World Scientific
Release Date : 2023-03-21
Artificial Intelligence For Science A Deep Learning Revolution written by Alok Choudhary and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Computers categories.
This unique collection introduces AI, Machine Learning (ML), and deep neural network technologies leading to scientific discovery from the datasets generated both by supercomputer simulation and by modern experimental facilities.Huge quantities of experimental data come from many sources — telescopes, satellites, gene sequencers, accelerators, and electron microscopes, including international facilities such as the Large Hadron Collider (LHC) at CERN in Geneva and the ITER Tokamak in France. These sources generate many petabytes moving to exabytes of data per year. Extracting scientific insights from these data is a major challenge for scientists, for whom the latest AI developments will be essential.The timely handbook benefits professionals, researchers, academics, and students in all fields of science and engineering as well as AI, ML, and neural networks. Further, the vision evident in this book inspires all those who influence or are influenced by scientific progress.
Hands On Artificial Intelligence With Tensorflow
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Author : Amir Ziai
language : en
Publisher:
Release Date : 2018-10-31
Hands On Artificial Intelligence With Tensorflow written by Amir Ziai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-31 with Artificial intelligence categories.
Book Description Artificial Intelligence (AI) is a popular area with an emphasis on creating intelligent machines that can reason, evaluate, and understand the same way as humans. It is used extensively across many fields, such as image recognition, robotics, language processing, healthcare, finance, and more. Hands-On Artificial Intelligence with TensorFlow gives you a rundown of essential AI concepts and their implementation with TensorFlow, also highlighting different approaches to solving AI problems using machine learning and deep learning techniques. In addition to this, the book covers advanced concepts, such as reinforcement learning, generative adversarial networks (GANs), and multimodal learning. Once you have grasped all this, you'll move on to exploring GPU computing and neuromorphic computing, along with the latest trends in quantum computing. You'll work through case studies that will help you examine AI applications in the important areas of computer vision, healthcare, and FinTech, and analyze their datasets. In the concluding chapters, you'll briefly investigate possible developments in AI that we can expect to see in the future. By the end of this book, you will be well-versed with the essential concepts of AI and their implementation using TensorFlow. What you will learn Explore the core concepts of AI and its different approaches Use the TensorFlow framework for smart applications Implement various machine and deep learning algorithms with TensorFlow Design self-learning RL systems and implement generative models Perform GPU computing efficiently using best practices Build enterprise-grade apps for computer vision, NLP, and healthcare Who this book is for Hands-On Artificial Intelligence with TensorFlow is for you if you are a machine learning developer, data scientist, AI researcher, or anyone who wants to build artificial intelligence applications using TensorFlow. You need to have some working knowledge of machine learning to get the most out of this book.
Artificial Intelligence Driven By Machine Learning And Deep Learning
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Author : Bahman Zohuri
language : en
Publisher: Nova Science Publishers
Release Date : 2020
Artificial Intelligence Driven By Machine Learning And Deep Learning written by Bahman Zohuri and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.
"The future of any business from banking, e-commerce, real estate, homeland security, healthcare, marketing, the stock market, manufacturing, education, retail to government organizations depends on the data and analytics capabilities that are built and scaled. The speed of change in technology in recent years has been a real challenge for all businesses. To manage that, a significant number of organizations are exploring the BigData (BD) infrastructure that helps them to take advantage of new opportunities while saving costs. Timely transformation of information is also critical for the survivability of an organization. Having the right information at the right time will enhance not only the knowledge of stakeholders within an organization but also providing them with a tool to make the right decision at the right moment. It is no longer enough to rely on a sampling of information about the organizations' customers. The decision-makers need to get vital insights into the customers' actual behavior, which requires enormous volumes of data to be processed. We believe that Big Data infrastructure is the key to successful Artificial Intelligence (AI) deployments and accurate, unbiased real-time insights. Big data solutions have a direct impact and changing the way the organization needs to work with help from AI and its components ML and DL. In this article, we discuss these topics"--
Artificial Intelligence Machine Learning And Deep Learning
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Author : Mark Howard
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-11-26
Artificial Intelligence Machine Learning And Deep Learning written by Mark Howard and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-26 with categories.
Have you ever wanted to learn how to better use your data? Are you interested in the works of machine learning? If you answered yes to these questions, then this book is for you. Artificial Intelligence, Machine Learning and Deep learning are powerful data tools that can help improve businesses. In this book, you will learn: Neural networks Machine learning How it relates to certain businesses What deep learning is Data handling Python and Machine Learning Examples of Machine Learning How Machine Learning is beneficial to you Learn about cognitive NLP Chatbots Learn about Cognitive NLP algorithms Discover about AI, deep learning, and Machine learning Understand the future AI solutions and adapt fast to them Computer vision Internet of Things Learn how recommender systems work Discover more about Robotics and Artificial intelligence. And much more Artificial Intelligence, Machine Learning and Deep learning are amazing tools when you want to use data in an effective manner. Data is important to many different areas in life, so it's important that you know how to use it. Don't let all of your data go to waste. Get this book today and improve the way your business works.
Deep Learning With Pytorch Lightning
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Author : Kunal Sawarkar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-04-29
Deep Learning With Pytorch Lightning written by Kunal Sawarkar 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 2022-04-29 with Computers categories.
Build, train, deploy, and scale deep learning models quickly and accurately, improving your productivity using the lightweight PyTorch Wrapper Key FeaturesBecome well-versed with PyTorch Lightning architecture and learn how it can be implemented in various industry domainsSpeed up your research using PyTorch Lightning by creating new loss functions, networks, and architecturesTrain and build new algorithms for massive data using distributed trainingBook Description PyTorch Lightning lets researchers build their own Deep Learning (DL) models without having to worry about the boilerplate. With the help of this book, you'll be able to maximize productivity for DL projects while ensuring full flexibility from model formulation through to implementation. You'll take a hands-on approach to implementing PyTorch Lightning models to get up to speed in no time. You'll start by learning how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. Next, you'll build a network and application from scratch and see how you can expand it based on your specific needs, beyond what the framework can provide. The book also demonstrates how to implement out-of-box capabilities to build and train Self-Supervised Learning, semi-supervised learning, and time series models using PyTorch Lightning. As you advance, you'll discover how generative adversarial networks (GANs) work. Finally, you'll work with deployment-ready applications, focusing on faster performance and scaling, model scoring on massive volumes of data, and model debugging. By the end of this PyTorch book, you'll have developed the knowledge and skills necessary to build and deploy your own scalable DL applications using PyTorch Lightning. What you will learnCustomize models that are built for different datasets, model architectures, and optimizersUnderstand how a variety of Deep Learning models from image recognition and time series to GANs, semi-supervised and self-supervised models can be builtUse out-of-the-box model architectures and pre-trained models using transfer learningRun and tune DL models in a multi-GPU environment using mixed-mode precisionsExplore techniques for model scoring on massive workloadsDiscover troubleshooting techniques while debugging DL modelsWho this book is for This deep learning book is for citizen data scientists and expert data scientists transitioning from other frameworks to PyTorch Lightning. This book will also be useful for deep learning researchers who are just getting started with coding for deep learning models using PyTorch Lightning. Working knowledge of Python programming and an intermediate-level understanding of statistics and deep learning fundamentals is expected.