Handbook Of Machine Learning Volume 1 Foundation Of Artificial Intelligence
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Handbook Of Machine Learning Volume 1 Foundation Of Artificial Intelligence
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Author : Tshilidzi Marwala
language : en
Publisher: World Scientific
Release Date : 2018-10-22
Handbook Of Machine Learning Volume 1 Foundation Of Artificial Intelligence written by Tshilidzi Marwala and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-22 with Computers categories.
This is a comprehensive book on the theories of artificial intelligence with an emphasis on their applications. It combines fuzzy logic and neural networks, as well as hidden Markov models and genetic algorithm, describes advancements and applications of these machine learning techniques and describes the problem of causality. This book should serves as a useful reference for practitioners in artificial intelligence.
Handbook Of Machine Learning
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Author : Tshilidzi Marwala
language : en
Publisher:
Release Date : 2019
Handbook Of Machine Learning written by Tshilidzi Marwala and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Artificial intelligence categories.
Handbook Of Machine Learning Volume 1 Foundation Of Artif
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Author : Tshilidzi Marwala
language : en
Publisher:
Release Date : 2018-12-22
Handbook Of Machine Learning Volume 1 Foundation Of Artif written by Tshilidzi Marwala and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-22 with categories.
Handbook Of Machine Learning Volume 2 Optimization And Decision Making
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Author : Tshilidzi Marwala
language : en
Publisher: World Scientific
Release Date : 2019-11-21
Handbook Of Machine Learning Volume 2 Optimization And Decision Making written by Tshilidzi Marwala and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-21 with Computers categories.
Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.
Artificial Intelligence And Machine Learning A Precise Book To Learn Basics
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Author : pc
language : en
Publisher: by Mocktime Publication
Release Date :
Artificial Intelligence And Machine Learning A Precise Book To Learn Basics written by pc and has been published by by Mocktime Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Artificial Intelligence and Machine Learning - A Precise Book to Learn Basics Table of Contents 1. Introduction to Artificial Intelligence and Machine Learning 1.1 What is Artificial Intelligence? 1.2 The Evolution of Artificial Intelligence 1.3 What is Machine Learning? 1.4 How Machine Learning Differs from Traditional Programming 1.5 The Importance of Artificial Intelligence and Machine Learning 2. Foundations of Machine Learning 2.1 Supervised Learning 2.1.1 Linear Regression 2.1.2 Logistic Regression 2.1.3 Decision Trees 2.2 Unsupervised Learning 2.2.1 Clustering 2.2.2 Dimensionality Reduction 2.3 Reinforcement Learning 2.3.1 Markov Decision Process 2.3.2 Q-Learning 3. Neural Networks and Deep Learning 3.1 Introduction to Neural Networks 3.2 Artificial Neural Networks 3.2.1 The Perceptron 3.2.2 Multi-Layer Perceptron 3.3 Convolutional Neural Networks 3.4 Recurrent Neural Networks 3.5 Generative Adversarial Networks 4. Natural Language Processing 4.1 Introduction to Natural Language Processing 4.2 Preprocessing and Text Representation 4.3 Sentiment Analysis 4.4 Named Entity Recognition 4.5 Text Summarization 5. Computer Vision 5.1 Introduction to Computer Vision 5.2 Image Processing 5.3 Object Detection 5.4 Image Segmentation 5.5 Face Recognition 6. Reinforcement Learning Applications 6.1 Reinforcement Learning in Robotics 6.2 Reinforcement Learning in Games 6.3 Reinforcement Learning in Finance 6.4 Reinforcement Learning in Healthcare 7. Ethics and Social Implications of Artificial Intelligence 7.1 Bias in Artificial Intelligence 7.2 The Future of Work 7.3 Privacy and Security 7.4 The Impact of AI on Society 8. Machine Learning Infrastructure 8.1 Cloud Infrastructure for Machine Learning 8.2 Distributed Machine Learning 8.3 DevOps for Machine Learning 9. Machine Learning Tools 9.1 Introduction to Machine Learning Tools 9.2 Python Libraries for Machine Learning 9.3 TensorFlow 9.4 Keras 9.5 PyTorch 10. Building and Deploying Machine Learning Models 10.1 Building a Machine Learning Model 10.2 Hyperparameter Tuning 10.3 Model Evaluation 10.4 Deployment Considerations 11. Time Series Analysis and Forecasting 11.1 Introduction to Time Series Analysis 11.2 ARIMA 11.3 Exponential Smoothing 11.4 Deep Learning for Time Series 12. Bayesian Machine Learning 12.1 Introduction to Bayesian Machine Learning 12.2 Bayesian Regression 12.3 Bayesian Classification 12.4 Bayesian Model Averaging 13. Anomaly Detection 13.1 Introduction to Anomaly Detection 13.2 Unsupervised Anomaly Detection 13.3 Supervised Anomaly Detection 13.4 Deep Learning for Anomaly Detection 14. Machine Learning in Healthcare 14.1 Introduction to Machine Learning in Healthcare 14.2 Electronic Health Records 14.3 Medical Image Analysis 14.4 Personalized Medicine 15. Recommender Systems 15.1 Introduction to Recommender Systems 15.2 Collaborative Filtering 15.3 Content-Based Filtering 15.4 Hybrid Recommender Systems 16. Transfer Learning 16.1 Introduction to Transfer Learning 16.2 Fine-Tuning 16.3 Domain Adaptation 16.4 Multi-Task Learning 17. Deep Reinforcement Learning 17.1 Introduction to Deep Reinforcement Learning 17.2 Deep Q-Networks 17.3 Actor-Critic Methods 17.4 Deep Reinforcement Learning Applications 18. Adversarial Machine Learning 18.1 Introduction to Adversarial Machine Learning 18.2 Adversarial Attacks 18.3 Adversarial Defenses 18.4 Adversarial Machine Learning Applications 19. Quantum Machine Learning 19.1 Introduction to Quantum Computing 19.2 Quantum Machine Learning 19.3 Quantum Computing Hardware 19.4 Quantum Machine Learning Applications 20. Machine Learning in Cybersecurity 20.1 Introduction to Machine Learning in Cybersecurity 20.2 Intrusion Detection 20.3 Malware Detection 20.4 Network Traffic Analysis 21. Future Directions in Artificial Intelligence and Machine Learning 21.1 Reinforcement Learning in Real-World Applications 21.2 Explainable Artificial Intelligence 21.3 Quantum Machine Learning 21.4 Autonomous Systems 22. Conclusion 22.1 Summary 22.2 Key Takeaways 22.3 Future Directions 22.4 Call to Action
The Handbook Of Artificial Intelligence
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Author : Avron Barr
language : en
Publisher: Butterworth-Heinemann
Release Date : 2014-05-12
The Handbook Of Artificial Intelligence written by Avron Barr and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-12 with Mathematics categories.
The Handbook of Artificial Intelligence, Volume I focuses on the progress in artificial intelligence (AI) and its increasing applications, including parsing, grammars, and search methods. The book first elaborates on AI, AI handbook and literature, problem representation, search methods, and sample search programs. The text then ponders on representation of knowledge, including survey of representation techniques and representation schemes. The manuscript explores understanding natural languages, as well as machine translation, grammars, parsing, test generation, and natural language processing systems. The book also takes a look at understanding spoken language, including systems architecture and the ARPA SUR projects. The text is a valuable source of information for computer science experts and researchers interested in pursuing further research in artificial intelligence.
Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques
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Author : Olivas, Emilio Soria
language : en
Publisher: IGI Global
Release Date : 2009-08-31
Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques written by Olivas, Emilio Soria and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-31 with Computers categories.
"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.
Handbook On Computer Learning And Intelligence In 2 Volumes
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Author : Plamen Parvanov Angelov
language : en
Publisher: World Scientific
Release Date : 2022-06-29
Handbook On Computer Learning And Intelligence In 2 Volumes written by Plamen Parvanov Angelov and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-29 with Computers categories.
The Handbook on Computer Learning and Intelligence is a second edition which aims to be a one-stop-shop for the various aspects of the broad research area of computer learning and intelligence. This field of research evolved so much in the last five years that it necessitates this new edition of the earlier Handbook on Computational Intelligence.This two-volume handbook is divided into five parts. Volume 1 covers Explainable AI and Supervised Learning. Volume 2 covers three parts: Deep Learning, Intelligent Control, and Evolutionary Computation. The chapters detail the theory, methodology and applications of computer learning and intelligence, and are authored by some of the leading experts in the respective areas. The fifteen core chapters of the previous edition have been written and significantly refreshed by the same authors. Parts of the handbook have evolved to keep pace with the latest developments in computational intelligence in the areas that span across Machine Learning and Artificial Intelligence. The Handbook remains dedicated to applications and engineering-orientated aspects of these areas over abstract theories.Related Link(s)
Handbook Of Research On Machine Learning
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Author : Monika Mangla
language : en
Publisher: CRC Press
Release Date : 2022-08-04
Handbook Of Research On Machine Learning written by Monika Mangla and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-04 with Computers categories.
This volume takes the reader on a technological voyage of machine learning advancements, highlighting the systematic changes in algorithms, challenges, and constraints. The technological advancements in the ML arena have transformed and revolutionized several fields, including transportation, agriculture, finance, weather monitoring, and others. This book brings together researchers, authors, industrialists, and academicians to cover a vast selection of topics in ML, starting with the rudiments of machine learning approaches and going on to specific applications in healthcare and industrial automation. The book begins with an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning as well as a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. Chapters explore predictive data analytics for health issues. The book also adds a macro dimension by highlighting the industrial applications of machine learning, such as in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.
The Ai Book
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Author : Ivana Bartoletti
language : en
Publisher: John Wiley & Sons
Release Date : 2020-06-29
The Ai Book written by Ivana Bartoletti and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Business & Economics categories.
Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important