Search Results - University of Konstanz~
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Teaching leaders to lead teachers educational administration in the era of constant crisis /
Published 2007Table of Contents: “…Introduction: teaching leaders to lead teachers: educational administration in the era of constant crisis / Saran Donahoo, Richard C. Hunter -- Becoming a leader of content knowledge / Alan C. …”
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New Trends in Mechanism and Machine Science Theory and Industrial Applications /
Published 2017Table of Contents: “…Sánchez -- Industrial and non-industrial applications 1 -- Winmecc: Software for the Analysis of Planar Mechanisms, by Antonio Ortiz, Juan Antonio Cabrera, Fernando Nadal and Alex Bataller -- Manipulator Motion Planning in Redundant Robotic System for Fiber Placement Process, by Jiuchun Gao, Anatol Pashkevich and Stéphane Caro -- Free and Open Source Software Applications for Education of TMM Discipline in Bauman University, by Andrei Vukolov -- A Novel One-DoF Gravity Balancer Based on Cardan Gear Mechanism, by Yu-Chun Hung and Chin-Hsing Kuo -- Galvanometer laser scanning: Custom-made input signals for maximum duty cycles in high-end imaging applications, by Virgil-Florin Duma -- Control issues -- Optimal Motion of Flexible Objects with Oscillations Elimination at the Stop Point, by Natalia Varminska and Damien Chablat -- Alternating Error Effects on Decomposition Method in Function Generation Synthesis, by Omar W Maaroof, Mehmet İsmet Can Dede and Gökhan Kiper -- Control-based Design of a Five-bar Mechanism, by Lila Kaci, Sébastien Briot, Clément Boudaud and Philippe Martinet -- History of mechanisms -- F. …”
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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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