Artificial Intelligence Driven by Machine Learning and Deep Learning:
Intro -- Contents -- Preface -- Acknowledgment -- Chapter 1 -- Artificial Intelligence -- 1.1. Introduction -- 1.2. History of Artificial Intelligence -- 1.3. Weak Artificial Intelligence (WAI) -- 1.3.1. And It Is Indeed a Possibility. The Signs Are All There -- 1.3.2. Technological Singularity -- 1...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York
Nova Science Publishers, Incorporated
2020
|
| Schriftenreihe: | Computer Science, Technology and Applications
|
| Schlagworte: | |
| Online-Zugang: | FWS01 FWS02 |
| Zusammenfassung: | Intro -- Contents -- Preface -- Acknowledgment -- Chapter 1 -- Artificial Intelligence -- 1.1. Introduction -- 1.2. History of Artificial Intelligence -- 1.3. Weak Artificial Intelligence (WAI) -- 1.3.1. And It Is Indeed a Possibility. The Signs Are All There -- 1.3.2. Technological Singularity -- 1.4. Artificial General Intelligence (AGI) -- 1.4.1. Existential Risk from Artificial General Intelligence -- 1.5. Natural Language Processing (NLP) -- 1.5.1. How Does NLP Work? -- 1.6. Cognitive Science and Cognitive Linguistics -- 1.7. Big Data -- 1.7.1. Big Data History and Current Considerations -- 1.7.2. What Are Big Data and Big Data Analytics? -- 1.7.3. Why Is Big Data Important? -- 1.7.4. Where Big Data Is Used and Who Uses it -- 1.7.5. How Does Big Data Work -- References -- Chapter 2 -- Machine Learning -- 2.1. Introduction -- 2.2. Problem Solving with Machine Learning -- 2.3. Estimating Probability Distributions -- 2.4. Linear Classifiers and Perceptron Algorithm -- 2.5. Decision Trees and Model Selection -- 2.6. Random Forest and How Does It Work -- 2.7. Overfitting in Decision Trees -- 2.8. Learning with Kernel Machines and Support Vector Machines -- 2.9. Debugging and Improving Machine Learning -- 2.10. Machine Learning Logistic (MLL) -- 2.11. Why Machine Learning -- 2.12. Machine Learning Boosting eCommerce -- 2.12.1. Eight Significant Applications of Machine Learning in eCommerce -- 2.12.2. Conclusion of Machine Learning and eCommerce -- References -- Chapter 3 -- Deep Learning -- 3.1. Introduction -- 3.2. Neural Networks Three Classes (MLP, CNN and RNN) -- 3.2.1. Multi-Layer Perceptrons (MLPs) -- 3.2.1.1. When to Use Multi-Layer Perceptrons (MLPs)? -- 3.2.2. Convolutional Neural Networks (CNNs) -- 3.2.2.1. When to Use Convolutional Neural Networks (CNNs)? -- 3.2.3. Recurrent Neural Networks (RNNs) |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (457 Seiten) |
| ISBN: | 9781536183672 |
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| 520 | 3 | |a Intro -- Contents -- Preface -- Acknowledgment -- Chapter 1 -- Artificial Intelligence -- 1.1. Introduction -- 1.2. History of Artificial Intelligence -- 1.3. Weak Artificial Intelligence (WAI) -- 1.3.1. And It Is Indeed a Possibility. The Signs Are All There -- 1.3.2. Technological Singularity -- 1.4. Artificial General Intelligence (AGI) -- 1.4.1. Existential Risk from Artificial General Intelligence -- 1.5. Natural Language Processing (NLP) -- 1.5.1. How Does NLP Work? -- 1.6. Cognitive Science and Cognitive Linguistics -- 1.7. Big Data -- 1.7.1. Big Data History and Current Considerations -- 1.7.2. What Are Big Data and Big Data Analytics? -- 1.7.3. Why Is Big Data Important? -- 1.7.4. Where Big Data Is Used and Who Uses it -- 1.7.5. How Does Big Data Work -- References -- Chapter 2 -- Machine Learning -- 2.1. Introduction -- 2.2. Problem Solving with Machine Learning -- 2.3. Estimating Probability Distributions -- 2.4. Linear Classifiers and Perceptron Algorithm -- 2.5. Decision Trees and Model Selection -- 2.6. Random Forest and How Does It Work -- 2.7. Overfitting in Decision Trees -- 2.8. Learning with Kernel Machines and Support Vector Machines -- 2.9. Debugging and Improving Machine Learning -- 2.10. Machine Learning Logistic (MLL) -- 2.11. Why Machine Learning -- 2.12. Machine Learning Boosting eCommerce -- 2.12.1. Eight Significant Applications of Machine Learning in eCommerce -- 2.12.2. Conclusion of Machine Learning and eCommerce -- References -- Chapter 3 -- Deep Learning -- 3.1. Introduction -- 3.2. Neural Networks Three Classes (MLP, CNN and RNN) -- 3.2.1. Multi-Layer Perceptrons (MLPs) -- 3.2.1.1. When to Use Multi-Layer Perceptrons (MLPs)? -- 3.2.2. Convolutional Neural Networks (CNNs) -- 3.2.2.1. When to Use Convolutional Neural Networks (CNNs)? -- 3.2.3. Recurrent Neural Networks (RNNs) | |
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| id | DE-604.BV047031093 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:02:18Z |
| indexdate | 2024-08-01T15:51:04Z |
| institution | BVB |
| isbn | 9781536183672 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032438364 |
| oclc_num | 1224484139 |
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| physical | 1 Online-Ressource (457 Seiten) |
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| publishDate | 2020 |
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| publisher | Nova Science Publishers, Incorporated |
| record_format | marc |
| series2 | Computer Science, Technology and Applications |
| spellingShingle | Zohuri, Bahman Zadeh, Siamak Artificial Intelligence Driven by Machine Learning and Deep Learning |
| title | Artificial Intelligence Driven by Machine Learning and Deep Learning |
| title_auth | Artificial Intelligence Driven by Machine Learning and Deep Learning |
| title_exact_search | Artificial Intelligence Driven by Machine Learning and Deep Learning |
| title_exact_search_txtP | Artificial Intelligence Driven by Machine Learning and Deep Learning |
| title_full | Artificial Intelligence Driven by Machine Learning and Deep Learning Bahman Zohuri and Siamak Zadeh |
| title_fullStr | Artificial Intelligence Driven by Machine Learning and Deep Learning Bahman Zohuri and Siamak Zadeh |
| title_full_unstemmed | Artificial Intelligence Driven by Machine Learning and Deep Learning Bahman Zohuri and Siamak Zadeh |
| title_short | Artificial Intelligence Driven by Machine Learning and Deep Learning |
| title_sort | artificial intelligence driven by machine learning and deep learning |
| work_keys_str_mv | AT zohuribahman artificialintelligencedrivenbymachinelearninganddeeplearning AT zadehsiamak artificialintelligencedrivenbymachinelearninganddeeplearning |