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Trade Unions on YouTube Online Revitalization in Sweden /
Published 2019Table of Contents: “…Introduction -- 2. Audiences: Who Do Unions Target? -- 3. Messages: Political Action - Agenda-Setting, Elections and Protest -- 4. …”
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Reading /
Published 2020Table of Contents: “…-- Section 1: What Is Engaged Reading? -- Section 2: How to Do This Kind of Engaged Reading? -- Things To Do -- On My Own -- Things to do on my own (1): Try the reading app -- Things to do on my own (2): Making notes or writing a reading diary -- Things to Do -- With Others -- Things to Do -- for Others -- Things to See and Hear -- Notes -- 5: What Can Professionals Do to Help? …”
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Future Studies and Counterfactual Analysis Seeds of the Future /
Published 2019Table of Contents: “…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.…”
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Man-eating monsters : anthropocentrism and popular culture /
Published 2019Full-text access
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From Bench to Boardroom The R&D Leader's Guide /
Published 2018Full-text access
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Deep Learning with Python, Second Edition.
Published 2021Table of Contents: “…-- 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.…”
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Digital materialism : origins, philosophies, prospects /
Published 2018Full-text access
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Urban Transformations Sustainable Urban Development Through Resource Efficiency, Quality of Life and Resilience /
Published 2018Table of Contents: “…-- 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? …”
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Generative AI with LangChain : Build Large Language Model (LLM) Apps with Python, ChatGPT, and Other LLMs.
Published 2023Table of Contents: “…-- Other LLMs -- Major players -- How do GPT models work? -- Pre-training -- Tokenization -- Scaling -- Conditioning -- How to try out these models -- What are text-to-image models? …”
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Gender and race matter global perspectives on being a woman.
Published 2016Full-text access
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