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A Generative Journey to AI : Mastering the foundations and frontiers of generative deep learning (English Edition) / / Toni Ramchandani
| A Generative Journey to AI : Mastering the foundations and frontiers of generative deep learning (English Edition) / / Toni Ramchandani |
| Autore | Ramchandani Toni |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Delhi : , : BPB Publications, , 2024 |
| Descrizione fisica | 1 online resource (378 pages) |
| Soggetto topico |
COMPUTERS / Intelligence (AI) & Semantics
COMPUTERS / Natural Language Processing COMPUTERS / Neural Networks |
| ISBN |
9789365893496
9365893496 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Generative Journey to AI : Mastering the foundations and frontiers of generative deep learning (English Edition) |
| Record Nr. | UNINA-9911117662903321 |
Ramchandani Toni
|
||
| Delhi : , : BPB Publications, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
AI in the Boardroom : Preparing Leaders for Responsible Governance
| AI in the Boardroom : Preparing Leaders for Responsible Governance |
| Autore | Petro Tom |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York : , : Business Expert Press, , 2025 |
| Descrizione fisica | 1 online resource (206 pages) |
| Disciplina | 658.4038028563 |
| Soggetto topico |
BUSINESS & ECONOMICS / Organizational Development*
BUSINESS & ECONOMICS / Corporate Governance COMPUTERS / Natural Language Processing |
| ISBN |
9781637427873
1637427875 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front cover -- Half title -- Title -- Copyright -- Description -- Contents -- Testimonials -- Foreword -- Preface -- Acknowledgments -- Introduction -- CHAPTER 1 The Case for Boardroom Oversight and Engagement -- The Impact of AI -- Strategic Boardroom Leadership of AI -- Performance -- Strategy -- Risk Management -- Purpose -- Board's Role in AI Governance -- New Risk Frontiers to Be Governed -- Inadequate AI Governance Is Costly -- Boardroom AI Expertise -- CHAPTER 2 An Introduction to AI -- Laying a Foundation -- A Framework for AI Governance -- CHAPTER 3 AI's Decision-Making Paradigms-Probabilistic or Deterministic -- Deterministic AI -- Probabilistic AI -- A Spectrum -- CHAPTER 4 Deciphering AI Risks -What Directors Should Know -- Bias and Discrimination -- Hallucinations -- Privacy and Security -- Ethics -- Safety and Reliability -- Transparency and Explainability -- Drift -- Missing Data -- Messy Data -- Unintended Consequences -- Social Impacts -- CHAPTER 5 A Primer on Data and Data Governance -- Elements of a Well-Developed Data Governance Framework -- Data Quality and Consistency -- Metadata Management -- Data Security -- Data Privacy -- Data Access and Usage -- Data Lifecycle Management -- Data Stewardship -- Commitment From the Top -- Understanding Data Types -- Data Quality -- Training Datasets Matter -- Synthetic Training and Validation Datasets -- The Board's Role in Data Governance -- CHAPTER 6 A Board Member's Guide to Core AI Techniques -- Symbolic Learning: Bridging Human Cognition and AI -- Key Board Risk Oversight Considerations for Symbolic Learning -- Symbolic Learning Decision-Making Paradigm -- Machine Learning: Unleashing the Power of Data -- Supervised Learning: Guided Discovery -- Key Board Risk Oversight Considerations for Supervised Machine Learning -- Supervised Learning Decision-Making Paradigm.
Unsupervised Learning: Unveiling Hidden Patterns -- Key Board Risk Oversight Considerations for Unsupervised Learning -- Unsupervised Learning Decision-Making Paradigm -- Reinforcement Learning: Learning Through Trial and Error -- Reinforcement Learning Decision-Making Paradigm -- Deep Learning: Harnessing the Power of Artifcial Neural Networks -- Key Board Risk Oversight Considerations for Deep Learning -- Deep Learning Decision-Making Paradigm -- Computer Vision: Seeing Through the Machine's Eye -- Key Board Risk Oversight Considerations for Computer Vision -- Computer Vision Decision-Making Paradigm -- Sensor Fusion: The Future of Intelligent Perception -- Key Board Risk Oversight Considerations for Sensor Fusion AI -- Sensor Fusion Decision-Making Paradigm -- Introducing Language-Based AI: Unlocking Language Intelligence -- The Shift to Small Language Models -- Generative AI Models -- LLMs in Generative AI -- Specialized Generative Models -- Generative AI in Other Domains -- Generative AI Versus LLMs and NLP -- Natural Language Processing: Empowering Machines to Speak and Comprehend -- Key Board Risk Oversight Issues for Natural Language Processing -- Natural Processing Language Decision-Making Paradigm -- Large Language Models: Harnessing the Power of Human Language -- Key Board Risk Oversight Considerations for Large Language Models -- Large Language Model Decision-Making Paradigm -- Generative AI: Unleashing the Power of Creation -- New Opportunities and Challenges -- Key Board Risk Oversight Issues for Generative AI -- Generative AI Model Decision-Making Paradigm -- Ensemble Learning -- Homogeneous Ensemble Learning -- Key Board Risk Oversight Considerations for Homogeneous Ensembles -- Multimodal Ensemble Learning -- Key Board Risk Oversight Considerations for Multimodal Ensembles -- Summary. CHAPTER 7 A Board Risk Management Framework for AI -- Embracing RAI Governance Principles -- Conduct a Readiness Assessment -- Data Governance -- Talent -- Core System Fitness -- Inventory of AI Uses -- Market Analysis -- Defensive Posture -- Workforce and Cultural Readiness -- Compliance Readiness -- Integrate AI Into Governance Frameworks -- Key Elements of AI Governance Framework -- Policy Scope and Objectives -- Business Strategy and Operating Plans -- Roles and Responsibilities -- Risk Appetite -- Risk Assessments -- Third-Party AI Systems -- Data Management -- AI Development Life Cycle -- Model and Training Data Validation -- Three Lines of Defense -- Incident Response -- Privacy and AI Regulatory Compliance -- Assurance and AI Audits -- Liability Insurance for AI -- Oversight Strategy -- Situationally Tailored Oversight -- Cultivating AI Governance Expertise -- Strategies for Cultivating AI Governance Expertise at the Board Level -- Rethinking Committee Structures -- Key Considerations for Committee Structures -- Strategies for Building AI Expertise Within the Ranks of Management -- Decisioning Framework -- Tracking Mechanisms -- Regular Progress Reports and Dashboards -- Reporting and Feedback Mechanisms -- Summary -- CHAPTER 8 A Board Director Call to Action -- Emerging Boardroom Considerations -- Evolving Case Law and Regulation -- Intellectual Property Considerations -- Evolving Regulatory Landscape -- Insurance and Liability -- AI Audits and Standards -- Security and Privacy Risks -- The Changing Role of Boards in the AI Era -- A Boardroom Imperative -- Appendix A Board Oversight Checklist for AI -- Appendix B Checklist for Third-Party AI Adoption -- Risk Assessment and Mapping -- Three Lines of Defense -- Vendor Due Diligence and Contractual Safeguards -- Monitoring and Auditing -- Transparency and Explainability. Human Oversight and Accountability -- Disclosure and Regulatory Compliance -- Continuous Improvement and Learning -- Appendix C Board Director Checklist for AI Data Governance -- Data Inventory and Mapping -- Data Quality and Integrity -- Data Security and Privacy -- Data Governance Framework -- Data for AI Development and Deployment -- Data Use in AI Models -- Data Sharing and Collaboration -- Board Oversight and Accountability -- Independent Audits and Reviews -- Appendix D Board Governance Checklist for Third-Party Data in AI -- Data Sourcing and Due Diligence -- Data Quality and Integrity -- Data Use and Ethical Considerations -- Third-Party Data for Proprietary Models -- Third-Party Data for External Models -- Contractual Safeguards for Third-Party Data -- Regulatory Compliance and Risk Management -- Board Oversight and Reporting -- Appendix E Governance Questions for Core AI Techniques -- Symbolic Learning -- Supervised Learning -- Unsupervised Learning -- Reinforcement learning -- Deep Learning -- Computer Vision -- Sensor Fusion -- Natural Language Processing -- Large Language Models -- Generative AI -- Homogeneous Ensemble Learning -- Multimodal Ensemble Learning -- Appendix F Root Causes of Bias in AI Models -- Biased Data -- Data Bias: Predictable Versus Masked -- Biased Algorithms -- Algorithmic Bias: Encoded Versus Distributed -- Biased Metrics -- Metrics Bias: Masked Accuracy Versus Misleading Uncertainty -- Biased Deployment -- Deployment Bias: Contextual Impact Versus Adaptive Interventions -- Appendix G Five Prominent Homogeneous Ensemble Learning Models -- Random Forest -- XGBoost -- Gradient Boosting Machine (GBM) -- Stacked Ensemble -- Bayesian Model Averaging (BMA) -- Appendix H Five Prominent Multimodal Ensemble Learning Models -- Multimodal Generative Models (e.g., GPT, DALL·E) -- Vision-Language Models (e.g., CLIP, Flamingo). Multimodal Transformers (e.g., ViLT, LXMERT) -- Multimodal Variational Autoencoders -- Multimodal Attention Networks (e.g., FLAVA) -- Glossary of AI Terminology -- References -- About the Author -- Index -- OTHER TITLES IN THE CORPORATE GOVERNANCE COLLECTION -- Concise and Applied Business Books -- Back cover. |
| Record Nr. | UNINA-9911117514203321 |
|
Petro Tom
|
||
| New York : , : Business Expert Press, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
AI in the Boardroom : Preparing Leaders for Responsible Governance
| AI in the Boardroom : Preparing Leaders for Responsible Governance |
| Autore | Petro Tom |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York : , : Business Expert Press, , 2025 |
| Descrizione fisica | 1 online resource (206 pages) |
| Disciplina | 658.4038028563 |
| Soggetto topico |
BUSINESS & ECONOMICS / Organizational Development*
BUSINESS & ECONOMICS / Corporate Governance COMPUTERS / Natural Language Processing |
| ISBN |
9781637427873
1637427875 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front cover -- Half title -- Title -- Copyright -- Description -- Contents -- Testimonials -- Foreword -- Preface -- Acknowledgments -- Introduction -- CHAPTER 1 The Case for Boardroom Oversight and Engagement -- The Impact of AI -- Strategic Boardroom Leadership of AI -- Performance -- Strategy -- Risk Management -- Purpose -- Board's Role in AI Governance -- New Risk Frontiers to Be Governed -- Inadequate AI Governance Is Costly -- Boardroom AI Expertise -- CHAPTER 2 An Introduction to AI -- Laying a Foundation -- A Framework for AI Governance -- CHAPTER 3 AI's Decision-Making Paradigms-Probabilistic or Deterministic -- Deterministic AI -- Probabilistic AI -- A Spectrum -- CHAPTER 4 Deciphering AI Risks -What Directors Should Know -- Bias and Discrimination -- Hallucinations -- Privacy and Security -- Ethics -- Safety and Reliability -- Transparency and Explainability -- Drift -- Missing Data -- Messy Data -- Unintended Consequences -- Social Impacts -- CHAPTER 5 A Primer on Data and Data Governance -- Elements of a Well-Developed Data Governance Framework -- Data Quality and Consistency -- Metadata Management -- Data Security -- Data Privacy -- Data Access and Usage -- Data Lifecycle Management -- Data Stewardship -- Commitment From the Top -- Understanding Data Types -- Data Quality -- Training Datasets Matter -- Synthetic Training and Validation Datasets -- The Board's Role in Data Governance -- CHAPTER 6 A Board Member's Guide to Core AI Techniques -- Symbolic Learning: Bridging Human Cognition and AI -- Key Board Risk Oversight Considerations for Symbolic Learning -- Symbolic Learning Decision-Making Paradigm -- Machine Learning: Unleashing the Power of Data -- Supervised Learning: Guided Discovery -- Key Board Risk Oversight Considerations for Supervised Machine Learning -- Supervised Learning Decision-Making Paradigm.
Unsupervised Learning: Unveiling Hidden Patterns -- Key Board Risk Oversight Considerations for Unsupervised Learning -- Unsupervised Learning Decision-Making Paradigm -- Reinforcement Learning: Learning Through Trial and Error -- Reinforcement Learning Decision-Making Paradigm -- Deep Learning: Harnessing the Power of Artifcial Neural Networks -- Key Board Risk Oversight Considerations for Deep Learning -- Deep Learning Decision-Making Paradigm -- Computer Vision: Seeing Through the Machine's Eye -- Key Board Risk Oversight Considerations for Computer Vision -- Computer Vision Decision-Making Paradigm -- Sensor Fusion: The Future of Intelligent Perception -- Key Board Risk Oversight Considerations for Sensor Fusion AI -- Sensor Fusion Decision-Making Paradigm -- Introducing Language-Based AI: Unlocking Language Intelligence -- The Shift to Small Language Models -- Generative AI Models -- LLMs in Generative AI -- Specialized Generative Models -- Generative AI in Other Domains -- Generative AI Versus LLMs and NLP -- Natural Language Processing: Empowering Machines to Speak and Comprehend -- Key Board Risk Oversight Issues for Natural Language Processing -- Natural Processing Language Decision-Making Paradigm -- Large Language Models: Harnessing the Power of Human Language -- Key Board Risk Oversight Considerations for Large Language Models -- Large Language Model Decision-Making Paradigm -- Generative AI: Unleashing the Power of Creation -- New Opportunities and Challenges -- Key Board Risk Oversight Issues for Generative AI -- Generative AI Model Decision-Making Paradigm -- Ensemble Learning -- Homogeneous Ensemble Learning -- Key Board Risk Oversight Considerations for Homogeneous Ensembles -- Multimodal Ensemble Learning -- Key Board Risk Oversight Considerations for Multimodal Ensembles -- Summary. CHAPTER 7 A Board Risk Management Framework for AI -- Embracing RAI Governance Principles -- Conduct a Readiness Assessment -- Data Governance -- Talent -- Core System Fitness -- Inventory of AI Uses -- Market Analysis -- Defensive Posture -- Workforce and Cultural Readiness -- Compliance Readiness -- Integrate AI Into Governance Frameworks -- Key Elements of AI Governance Framework -- Policy Scope and Objectives -- Business Strategy and Operating Plans -- Roles and Responsibilities -- Risk Appetite -- Risk Assessments -- Third-Party AI Systems -- Data Management -- AI Development Life Cycle -- Model and Training Data Validation -- Three Lines of Defense -- Incident Response -- Privacy and AI Regulatory Compliance -- Assurance and AI Audits -- Liability Insurance for AI -- Oversight Strategy -- Situationally Tailored Oversight -- Cultivating AI Governance Expertise -- Strategies for Cultivating AI Governance Expertise at the Board Level -- Rethinking Committee Structures -- Key Considerations for Committee Structures -- Strategies for Building AI Expertise Within the Ranks of Management -- Decisioning Framework -- Tracking Mechanisms -- Regular Progress Reports and Dashboards -- Reporting and Feedback Mechanisms -- Summary -- CHAPTER 8 A Board Director Call to Action -- Emerging Boardroom Considerations -- Evolving Case Law and Regulation -- Intellectual Property Considerations -- Evolving Regulatory Landscape -- Insurance and Liability -- AI Audits and Standards -- Security and Privacy Risks -- The Changing Role of Boards in the AI Era -- A Boardroom Imperative -- Appendix A Board Oversight Checklist for AI -- Appendix B Checklist for Third-Party AI Adoption -- Risk Assessment and Mapping -- Three Lines of Defense -- Vendor Due Diligence and Contractual Safeguards -- Monitoring and Auditing -- Transparency and Explainability. Human Oversight and Accountability -- Disclosure and Regulatory Compliance -- Continuous Improvement and Learning -- Appendix C Board Director Checklist for AI Data Governance -- Data Inventory and Mapping -- Data Quality and Integrity -- Data Security and Privacy -- Data Governance Framework -- Data for AI Development and Deployment -- Data Use in AI Models -- Data Sharing and Collaboration -- Board Oversight and Accountability -- Independent Audits and Reviews -- Appendix D Board Governance Checklist for Third-Party Data in AI -- Data Sourcing and Due Diligence -- Data Quality and Integrity -- Data Use and Ethical Considerations -- Third-Party Data for Proprietary Models -- Third-Party Data for External Models -- Contractual Safeguards for Third-Party Data -- Regulatory Compliance and Risk Management -- Board Oversight and Reporting -- Appendix E Governance Questions for Core AI Techniques -- Symbolic Learning -- Supervised Learning -- Unsupervised Learning -- Reinforcement learning -- Deep Learning -- Computer Vision -- Sensor Fusion -- Natural Language Processing -- Large Language Models -- Generative AI -- Homogeneous Ensemble Learning -- Multimodal Ensemble Learning -- Appendix F Root Causes of Bias in AI Models -- Biased Data -- Data Bias: Predictable Versus Masked -- Biased Algorithms -- Algorithmic Bias: Encoded Versus Distributed -- Biased Metrics -- Metrics Bias: Masked Accuracy Versus Misleading Uncertainty -- Biased Deployment -- Deployment Bias: Contextual Impact Versus Adaptive Interventions -- Appendix G Five Prominent Homogeneous Ensemble Learning Models -- Random Forest -- XGBoost -- Gradient Boosting Machine (GBM) -- Stacked Ensemble -- Bayesian Model Averaging (BMA) -- Appendix H Five Prominent Multimodal Ensemble Learning Models -- Multimodal Generative Models (e.g., GPT, DALL·E) -- Vision-Language Models (e.g., CLIP, Flamingo). Multimodal Transformers (e.g., ViLT, LXMERT) -- Multimodal Variational Autoencoders -- Multimodal Attention Networks (e.g., FLAVA) -- Glossary of AI Terminology -- References -- About the Author -- Index -- OTHER TITLES IN THE CORPORATE GOVERNANCE COLLECTION -- Concise and Applied Business Books -- Back cover. |
| Record Nr. | UNINA-9911132667603321 |
| Petro Tom | ||
| New York : , : Business Expert Press, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence and Financial Security : Harnessing AI to protect and optimize financial systems (English Edition) / / Piyush Ranjan, Brij Pandey, Rajiv Avacharmal
| Artificial Intelligence and Financial Security : Harnessing AI to protect and optimize financial systems (English Edition) / / Piyush Ranjan, Brij Pandey, Rajiv Avacharmal |
| Autore | Ranjan Piyush |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Delhi : , : BPB Publications, , 2024 |
| Descrizione fisica | 1 online resource (284 pages) |
| Altri autori (Persone) |
PandeyBrij Kishore
AvacharmalRajiv |
| Soggetto topico |
COMPUTERS / Intelligence (AI) & Semantics
COMPUTERS / Desktop Applications / Personal Finance Applications COMPUTERS / Natural Language Processing |
| ISBN |
9789365895308
9365895308 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Artificial Intelligence and Financial Security : Harnessing AI to protect and optimize financial systems (English Edition) |
| Record Nr. | UNINA-9911117657203321 |
|
Ranjan Piyush
|
||
| Delhi : , : BPB Publications, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence and Financial Security : Harnessing AI to protect and optimize financial systems (English Edition) / / Piyush Ranjan, Brij Pandey, Rajiv Avacharmal
| Artificial Intelligence and Financial Security : Harnessing AI to protect and optimize financial systems (English Edition) / / Piyush Ranjan, Brij Pandey, Rajiv Avacharmal |
| Autore | Ranjan Piyush |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | BPB Publications, 2024 |
| Descrizione fisica | 1 online resource (284 pages) |
| Disciplina | 004.678 |
| Altri autori (Persone) |
PandeyBrij Kishore
AvacharmalRajiv |
| Soggetto topico |
COMPUTERS / Intelligence (AI) & Semantics
COMPUTERS / Desktop Applications / Personal Finance Applications COMPUTERS / Natural Language Processing |
| ISBN |
9789365895308
9365895308 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Artificial Intelligence and Financial Security : Harnessing AI to protect and optimize financial systems (English Edition) |
| Record Nr. | UNINA-9911132582803321 |
| Ranjan Piyush | ||
| BPB Publications, 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
A Generative Journey to AI : Mastering the foundations and frontiers of generative deep learning (English Edition) / / Toni Ramchandani
| A Generative Journey to AI : Mastering the foundations and frontiers of generative deep learning (English Edition) / / Toni Ramchandani |
| Autore | Ramchandani Toni |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | BPB Publications, 2024 |
| Descrizione fisica | 1 online resource (378 pages) |
| Disciplina | 006.3 |
| Soggetto topico |
COMPUTERS / Intelligence (AI) & Semantics
COMPUTERS / Natural Language Processing COMPUTERS / Neural Networks |
| ISBN |
9789365893496
9365893496 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Generative Journey to AI : Mastering the foundations and frontiers of generative deep learning (English Edition) |
| Record Nr. | UNINA-9911132585403321 |
| Ramchandani Toni | ||
| BPB Publications, 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Natural Language Processing Fundamentals for Developers
| Natural Language Processing Fundamentals for Developers |
| Autore | Campesato Oswald |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2021 |
| Descrizione fisica | 1 online resource (382 pages) |
| Disciplina | 006.35 |
| Soggetto topico | COMPUTERS / Natural Language Processing |
| Soggetto non controllato |
Computer Science
Data Analytics Machine Learning Natural Language Processing |
| ISBN |
1-68392-655-2
1-68392-656-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | NLPFD.Ch00.FM.pdf -- NLPFD.Ch1.pdf -- NLPFD.Ch2.pdf -- NLPFD.Ch3.pdf -- NLPFD.Ch4.pdf -- NLPFD.Ch5.pdf -- NLPFD.Ch6.pdf -- NLPFD.Ch7.pdf -- NLPFD.Ch8.AppA.pdf -- NLPFD.Ch9.AppB.pdf. |
| Record Nr. | UNINA-9910795874703321 |
|
Campesato Oswald
|
||
| Bloomfield : , : Mercury Learning & Information, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Natural Language Processing Fundamentals for Developers
| Natural Language Processing Fundamentals for Developers |
| Autore | Campesato Oswald |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Bloomfield : , : Mercury Learning & Information, , 2021 |
| Descrizione fisica | 1 online resource (382 pages) |
| Disciplina | 006.35 |
| Soggetto topico | COMPUTERS / Natural Language Processing |
| Soggetto non controllato |
Computer Science
Data Analytics Machine Learning Natural Language Processing |
| ISBN |
1-68392-655-2
1-68392-656-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | NLPFD.Ch00.FM.pdf -- NLPFD.Ch1.pdf -- NLPFD.Ch2.pdf -- NLPFD.Ch3.pdf -- NLPFD.Ch4.pdf -- NLPFD.Ch5.pdf -- NLPFD.Ch6.pdf -- NLPFD.Ch7.pdf -- NLPFD.Ch8.AppA.pdf -- NLPFD.Ch9.AppB.pdf. |
| Record Nr. | UNINA-9910812890203321 |
|
Campesato Oswald
|
||
| Bloomfield : , : Mercury Learning & Information, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
