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  • Eclipse is the leading Integrated Development Environment (IDE) for Java, with a rich ecosystem of

    Eclipse is the leading Integrated Development Environment (IDE) for Java, with a rich ecosystem of plug-ins and an open source framework that supports other languages and projects. You’ll fnd this reference card useful for getting started with Eclipse and exploring the breadth of its features. We rundown the Eclipse distributions and confguration options, then guide you through Views, Editors, and Perspec- tives in Workbench 101. We list the top shortcuts and toolbar actions for everyday development. And, we provide a guide to the best places for fnding plug-ins and getting involved with the Eclipse community.

    標簽： Development Environment Integrated ecosystem

    上傳時間： 2013-12-18

    上傳用戶：wangchong

  • C++ is considered the most widely used and powerful object-oriented programming language in industry

    C++ is considered the most widely used and powerful object-oriented programming language in industry today. This book is for who are interested in learning and exploring C++ programming where programs are developed to interface with real world devices. Learning C++ for interact with various hardware devices and how to interface a computer to physical devices. Anyone who is simply interested in programming and interfacing a computer to perform real activities.

    標簽： object-oriented programming considered industry

    上傳時間： 2017-08-13

    上傳用戶：gmh1314

  • interpretable-machine-learning

    Machinelearninghasgreatpotentialforimprovingproducts,processesandresearch.Butcomputers usually do not explain their predictions which is a barrier to the adoption of machine learning. This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model- agnosticmethodsforinterpretingblackboxmodelslikefeatureimportanceandaccumulatedlocal effects and explaining individual predictions with Shapley values and LIME.

    標簽： interpretable-machine-learning

    上傳時間： 2020-06-10

    上傳用戶：shancjb

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