Sisällysluettelo:
“…Samset -- 2.5 Clouds / Paulo Ceppi -- 2.6 Arctic warming and the jet stream / Jennifer Francis -- 2.7 Dangerous weather / Friederike Otto -- 2.8 ‘The snowball has been set in motion’ / Greta Thunberg -- 2.9 Droughts and floods / Kate Marvel -- 2.10 Ice sheets, shelves and glaciers / Ricarda Winkelmann -- 2.11 Warming oceans and rising seas / Stefan Rahmstorf -- 2.12 Acidification and marine ecosystems / Hans-Otto Pörtner -- 2.13 Microplastics / Karin Kvale -- 2.14 Fresh water / Peter H. …”
Sisällysluettelo:
“…Part IV Lectometric methodology -- 7 Quantifying lectal structure and change -- 7.1 Measuring lectal distances -- 7.2 Standardization and informalization -- 7.3 Lexical diversity and lexical success -- The bottom line -- 8 Lectometry step by step -- 8.1 Selection of near-synonyms -- 8.2 Demarcation of the model space -- 8.3 Fine-tuning profiles -- 8.4 Selection of pruned models -- 8.5 Lectometric measures -- The bottom line -- Part V Lectometric explorations -- 9 Dimensions of standardization -- 9.1 Corpora and concepts -- 9.2 Modelling of token spaces and selection of profiles -- 9.3 Hierarchical standardization and destandardization -- 9.4 Formalization and informalization -- 9.5 Homogenization and dehomogenization -- 9.6 The evolution of Belgian and Netherlandic Dutch -- The bottom line -- 10 Pluricentricity from a quantitative point of view -- 10.1 Spanish as an international language -- 10.2 Corpus and concept selection -- 10.3 Distributional modelling -- 10.4 The impact of model retention -- 10.5 The impact of lexical fields -- 10.6 Pluricentricity and the plurality of models -- The bottom line -- Conclusions -- Software resources -- References -- Index…”
Sisällysluettelo:
“…7.3 Structuring data-driven innovation management -- 7.4 Innovation management summary -- Notes -- 08 Leadership and Governance -- 8.1 Introduction to leadership and governance -- 8.2 Purpose and maturity levels of leadership and governance -- 8.3 Structuring leadership and governance -- 8.4 Leadership and governance summary -- Notes -- 09 Communication -- 9.1 Introduction to communication -- 9.2 Purpose and maturity levels of communication -- 9.3 Structuring communication -- 9.4 Communication summary -- Notes -- 10 Sustainability -- 10.1 Introduction to sustainability -- 10.2 Purpose and maturity levels of sustainability -- 10.3 Structuring sustainability -- 10.4 Sustainability summary -- Notes -- 11 Programme Funding -- 11.1 Introduction to programme funding -- 11.2 Purpose and maturity levels of programme funding -- 11.3 Structuring programme funding -- 11.4 Programme funding summary -- Note -- 12 Big Data Strategy Maturity Assessment -- PART FOUR Designing a Big Data Architecture -- 13 Big Data Architecture -- 13.1 Introduction to Big Data architecture -- 13.2 Fundamental structure of Big Data architecture -- 13.3 Purpose and structure of Big Data architecture -- 13.4 The NIST Big Data Reference Architecture -- 13.5 Value chains of the NBDRA -- 13.6 The five main roles of the NBDRA -- 13.7 The two fabrics of the NBDRA -- 13.8 Other Big Data architecture standards -- Notes -- 14 Big Data Architecture Management -- 14.1 Introduction to Big Data architecture management -- 14.2 Purpose and maturity levels of Big Data architecture management -- 14.3 Structuring Big Data architecture management -- 14.4 Big Data architecture management summary -- Note -- 15 Infrastructure Management -- 15.1 Introduction to infrastructure management -- 15.2 Purpose and maturity levels of infrastructure management -- 15.3 Structuring infrastructure management…”
Sisällysluettelo:
“…-- 4 Global Perspectives on Law and Governance of SLCPs -- 5 Case Studies on SLCP Mitigation -- Acknowledgements -- Bibliography -- Chapter 1 Scientific Overview on SLCPs: Characteristics, Impacts and Uncertainties -- 1 Introduction -- 2 Radiative Forcing and Surface Air Temperature -- 2.1 The Radiative Balance of the Earth System -- 2.2 Climate Feedbacks and Climate Response -- 3 Short- Lived Climate Pollutants -- 3.1 Carbon Dioxide -- 3.2 Ozone (O3) -- 3.3 Methane -- 3.4 Hydrofluorocarbons (HFCs) -- 3.5 Aerosols and Black Carbon -- 3.5.1 Black Carbon and Albedo Effects -- 3.6 Present- Day and Historical Effects of SLCPs -- 3.6.1 Present- Day Health Effects Due to SLCFs -- 4 Climate Modelling of SLCFs -- 4.1 Structure of Climate Models -- 4.2 Simulating the SLCFs in Climate Models -- 4.3 Estimating Radiative Forcing from Climate Model Simulations -- 5 Future Effects of SLCFs -- 6 Uncertainties -- 7 Conclusion -- Bibliography -- Part 1 Global Perspectives on Law and Policy of SLCP s -- Chapter 2 A Conceptual History of SLCP s -- 1 Introduction -- 1.1 Theoretical Background -- 1.2 Methodology -- 2 Linking Climate Change and Air Pollution: 1990s-2000s -- 2.1 Early Discoveries: Black Carbon and the Asian Brown Cloud -- 2.2 Taking a Closer Look at Trace Gases: Methane and HFCs Re-examined -- 2.3 Reframing Climate Change for the 21st Century -- 3 The Concept's Arctic Origins: 2007-9 -- 3.1 AMAP's Contributions to the SLCP Debate -- 3.2 Wider Political Impact of Arctic Research…”
Sisällysluettelo:
“…-- Unit Testing for Model Training and Serving -- Testing for Updates in API Calls -- Testing for Algorithmic Correctness -- Summary -- Exam Essentials -- Review Questions -- Chapter 9 Model Explainability on Vertex AI -- Model Explainability on Vertex AI -- Explainable AI -- Interpretability and Explainability -- Feature Importance -- Vertex Explainable AI -- Data Bias and Fairness -- ML Solution Readiness -- How to Set Up Explanations in the Vertex AI -- Summary -- Exam Essentials -- Review Questions -- Chapter 10 Scaling Models in Production -- Scaling Prediction Service -- TensorFlow Serving -- Serving (Online, Batch, and Caching) -- Real-Time Static and Dynamic Reference Features -- Pre-computing and Caching Prediction -- Google Cloud Serving Options -- Online Predictions -- Batch Predictions -- Hosting Third-Party Pipelines (MLflow) on Google Cloud -- Testing for Target Performance -- Configuring Triggers and Pipeline Schedules -- Summary -- Exam Essentials -- Review Questions -- Chapter 11 Designing ML Training Pipelines -- Orchestration Frameworks -- Kubeflow Pipelines -- Vertex AI Pipelines -- Apache Airflow -- Cloud Composer -- Comparison of Tools -- Identification of Components, Parameters, Triggers, and Compute Needs -- Schedule the Workflows with Kubeflow Pipelines -- Schedule Vertex AI Pipelines -- System Design with Kubeflow/TFX -- System Design with Kubeflow DSL -- System Design with TFX -- Hybrid or Multicloud Strategies -- Summary -- Exam Essentials -- Review Questions -- Chapter 12 Model Monitoring, Tracking, and Auditing Metadata -- Model Monitoring -- Concept Drift -- Data Drift -- Model Monitoring on Vertex AI -- Drift and Skew Calculation -- Input Schemas -- Logging Strategy -- Types of Prediction Logs -- Log Settings -- Model Monitoring and Logging -- Model and Dataset Lineage…”