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云、移动端和边缘智能设备的实用深度学习(影印版)

云、移动端和边缘智能设备的实用深度学习(影印版)

出版社:东南大学出版社出版时间:2020-06-01
开本: 其他 页数: 588
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云、移动端和边缘智能设备的实用深度学习(影印版) 版权信息

  • ISBN:9787564188825
  • 条形码:9787564188825 ; 978-7-5641-8882-5
  • 装帧:平装-胶订
  • 册数:暂无
  • 重量:暂无
  • 所属分类:>

云、移动端和边缘智能设备的实用深度学习(影印版) 本书特色

无论你是一名渴望进入人工智能世界的软件工程师,一名经验丰富的数据科学家,还是一名怀揣创造下一个人工智能爆款应用伟大梦想的业余爱好者,你可能都想知道从哪里开始深度学习。这本循序渐进的指导书会教你如何通过实际动手操作的方式为云计算、移动端、浏览器和边缘设备构建实用的深度学习应用程序。

云、移动端和边缘智能设备的实用深度学习(影印版) 内容简介

无论你是一名渴望进入人工智能世界的软件工程师,一名经验丰富的数据科学家,还是一名怀揣创造下一个人工智能爆款应用伟大梦想的业余爱好者,你可能都想知道从哪里开始深度学习。这本循序渐进的指导书会教你如何通过实际动手操作的方式为云计算、移动端、浏览器和边缘设备构建实用的深度学习应用程序。

云、移动端和边缘智能设备的实用深度学习(影印版) 目录

Preface 1. Exploring the Landscape of Artificial Intelligence An Apology The Real Introduction What Is AI? Motivating Examples A Brief History of AI Exciting Beginnings The Cold and Dark Days A Glimmer of Hope How Deep Learning Became a Thing Recipe for the Perfect Deep Learning Solution Datasets Model Architecture Frameworks Hardware Responsible AI Bias Accountability and Explainability Reproducibility Robustness Privacy Summary Frequently Asked Questions 2. What's in the Picture: Image Classification with Keras Introducing Keras Predicting an Image's Category Investigating the Model ImageNet Dataset Model Zoos Class Activation Maps Summary 3. Cats Versus Dogs: Transfer Learning in 30 Lines with Keras Adapting Pretrained Models to New Tasks A Shallow Dive into Convolutional Neural Networks Transfer Learning Fine Tuning How Much to Fine Tune Building a Custom Classifier in Keras with Transfer Learning Organize the Data Build the Data Pipeline Number of Classes Batch Size Data Augmentation Model Definition Train the Model Set Training Parameters Start Training Test the Model Analyzing the Results Further Reading Summary 4. Building a Reverse Image Search Engine: Understanding Embedflings Image Similarity Feature Extraction Similarity Search Visualizing Image Clusters with t-SNE Improving the Speed of Similarity Search Length of Feature Vectors Reducing Feature-Length with PCA Scaling Similarity Search with Approximate Nearest Neighbors Approximate Nearest-Neighbor Benchmark …… 5. From Novice to Master Predictor: Maximizing Convolutional Neural Network Accuracy 6. Maximizing Speed and Performance of TensorFlow: A Handy Checklist 7. Practical Tools, Tips, and Tricks 8. Cloud APIs for Computer Vision: Up and Running in 15 Minutes 9. Scalable Inference Serving on Cloud with TensorFlow Serving and KubeFlow 10. AI in the Browser with TensorFlow. js and ml5.js 11. Real-Time Object Classification on iOS with Core ML 12. Not Hotdog on iOS with Core ML and Create ML 13. Shazam for Food: Developing Android Apps with TensorFlow Lite and ML Kit 14. Building the Purrfect Cat Locator App with TensorFlow Object Detection API 15. Becoming a Maker: Exploring Embedded AI at the edge 16. Simulating a Self-Driving Car Using End-to-End Deep Learning with Keras 17. Building an Autonomous Car in Under and Hour: Reinforcement Learning with AWS DeepRacer A. A Crash Course in Convolutional Neural Networks Index
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