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Project tracking systems, test and build tools, source control, continuous integration, and other built-in parts of the software development lifecycle generate a wealth of data that can be used to track and improve the quality and performance of products, processes, and teams. Although the iterative nature of Agile development is perfect for data-driven continuous improvement, the collection, analysis, and application of meaningful metrics often fades in favor of subjective measures that offer less insight into the real challenges of making better software. Agile Metrics in Action: Measuring and enhancing the performance of Agile teams is a practical book that shows how to take the data already being generated to make teams, processes, and products better. It points out which metrics to use to objectively measure performance and what data really counts, along with where to find it, how to get it, and how to analyze it. The book also shows how all team members can publish their own metrics through dashboards and radiators, taking charge of communicating performance and individual accountability. Along the way, it offers practical data analysis techniques, including a few emerging Big Data practices. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Table of Contents Part 1 Measuring agile teams Chapter 1 Measuring agile performance Chapter 2 Observing a live project Part 2 Collecting and analyzing your team’s data Chapter 3 Trends and data from project-tracking systems Chapter 4 Trends and data from source control Chapter 5 Trends and data from CI and deployment servers Chapter 6 Data from your production systems Part 3 Applying metrics to your teams, processes, and software Chapter 7 Working with the data you’re collecting: the sum of the parts Chapter 8 Measuring the technical quality of your software Chapter 9 Publishing metrics Chapter 10 Measuring your team against the agile principles Appendix A D

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D3.js in Action, Second Edition is completely revised and updated for D3 v4 and ES6. It's a practical tutorial for creating interactive graphics and data-driven applications using D3. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Visualizing complex data is hard. Visualizing complex data on the web is darn near impossible without D3.js. D3 is a JavaScript library that provides a simple but powerful data visualization API over HTML, CSS, and SVG. Start with a structure, dataset, or algorithm; mix in D3; and you can programmatically generate static, animated, or interactive images that scale to any screen or browser. It's easy, and after a little practice, you'll be blown away by how beautiful your results can be! About the Book D3.js in Action, Second Edition is a completely updated revision of Manning's bestselling guide to data visualization with D3. You'll explore dozens of real-world examples, including force and network diagrams, workflow illustrations, geospatial constructions, and more. Along the way, you'll pick up best practices for building interactive graphics, animations, and live data representations. You'll also step through a fully interactive application created with D3 and React. What's Inside Updated for D3 v4 and ES6 Reusable layouts and components Geospatial data visualizations Mixed-mode rendering About the Reader Suitable for web developers with HTML, CSS, and JavaScript skills. No specialized data science skills required. About the Author

| 英语 PaddleVideo 介绍 PaddleVideo是用于为行业和学术界准备的视频识别，动作本地化和时空动作检测任务的工具集。 该存储库提供了示例和最佳实践指南，用于在视频区域的场景中探索深度学习算法。 我们致力于支持可以大大减少“部署时间”的实验和实用程序。 顺便说一句，这也是视频领域最新PaddlePaddle 2.0的熟练度验证和实现。 特征 先进的模型动物园设计PaddleVideo统一了视频理解任务，包括识别，本地化，时空行为检测等。 借助基于IOC / DI的清晰配置系统，我们设计了一个去耦模块化和可扩展的框架，该框架可以通过组合不同的模块轻松构建自定义网络。 各种数据集和体系架构PaddleVideo支持多个数据集和架构，包括 ，ucf101，YoutTube8M数据集和视频识别模型，诸如TSN，TSM，SlowFast，AttentionLSTM和行动本地化模

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Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI. About the Technology Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before.