Arama Sonuçları - "\"((\\"do NOT adjust four set\\") OR (\\"do NOT adjust our set\\"))*\""

Reading / Yazar: Davis, Philip (Philip Maurice), Magee, Fiona

Full-text access
OPAC'ta görüntüle

Man-eating monsters : anthropocentrism and popular culture /

Full-text access
OPAC'ta görüntüle

Future Studies and Counterfactual Analysis Seeds of the Future / Yazar: Gordon, Theodore J., Todorova, Mariana

İçindekiler: “…Civility is Almost Gone, Debate is Almost Non-existent, yet the Sides are Firm in Their Positions and Sure They are Right -- Chapter 13: The Perfect Human: Unlocking the Mysteries of Human Genetics and Developing the Technologies to Manipulate Heredity Will Give, for Better or Worse, a New Dimension to Our Ability toSet the Fate of Our Children -- Chapter 14: Conclusions -- Appendix A Methodologies -- Appendix B Authors' Biographies -- Index.…”
Full-text access
OPAC'ta görüntüle

Urban Transformations Sustainable Urban Development Through Resource Efficiency, Quality of Life and Resilience /

İçindekiler: “…-- Adapting built-up areas to climate change - assessment of effects and feasibility of adaptation measures on thermal comfort -- Climate proofing in urban planning and permitting - a key to resilient urban development -- Decision support on natural hazards management in complex urban settings -- Is risk assessment the right approach or do we need decision heuristics? …”
Full-text access
OPAC'ta görüntüle

Resilience to Climate Change Communication, Collaboration and Co-production / Yazar: Howarth, Candice

Full-text access
OPAC'ta görüntüle

The cryopolitics of reproduction on ice : a new Scandinavian ice age / Yazar: Kroløkke, Charlotte, Petersen, Thomas Søbirk, Herrmann, Janne Rothmar, Bach, Anna Sofie, Adrian, Stine Willum, Hansen, Rune Klingenberg, Petersen, Michael Nebeling

Full-text access
OPAC'ta görüntüle

Deep Learning with Python, Second Edition. Yazar: Chollet, Francois

İçindekiler: “…-- 3.3 Keras and TensorFlow: A brief history -- 3.4 Setting up a deep learning workspace -- 3.4.1 Jupyter notebooks: The preferred way to run deep learning experiments -- 3.4.2 Using Colaboratory -- 3.5 First steps with TensorFlow -- 3.5.1 Constant tensors and variables -- 3.5.2 Tensor operations: Doing math in TensorFlow -- 3.5.3 A second look at the GradientTape API -- 3.5.4 An end-to-end example: A linear classifier in pure TensorFlow -- 3.6 Anatomy of a neural network: Understanding core Keras APIs -- 3.6.1 Layers: The building blocks of deep learning -- 3.6.2 From layers to models -- 3.6.3 The "compile" step: Configuring the learning process -- 3.6.4 Picking a loss function -- 3.6.5 Understanding the fit() method -- 3.6.6 Monitoring loss and metrics on validation data -- 3.6.7 Inference: Using a model after training -- Summary -- 4 Getting started with neural networks: Classification and regression -- 4.1 Classifying movie reviews: A binary classification example -- 4.1.1 The IMDB dataset -- 4.1.2 Preparing the data -- 4.1.3 Building your model -- 4.1.4 Validating your approach.…”
Full-text access
OPAC'ta görüntüle

Transforming virtual world learning

Full-text access
OPAC'ta görüntüle