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深度學習
云、移動端和邊緣智能設備的實用深度學習(影印版) 版權信息
- ISBN:9787564188825
- 條形碼:9787564188825 ; 978-7-5641-8882-5
- 裝幀:平裝-膠訂
- 冊數:暫無
- 重量:暫無
- 所屬分類:>
云、移動端和邊緣智能設備的實用深度學習(影印版) 本書特色
無論你是一名渴望進入人工智能世界的軟件工程師,一名經驗豐富的數據科學家,還是一名懷揣創造下一個人工智能爆款應用偉大夢想的業余愛好者,你可能都想知道從哪里開始深度學習。這本循序漸進的指導書會教你如何通過實際動手操作的方式為云計算、移動端、瀏覽器和邊緣設備構建實用的深度學習應用程序。
云、移動端和邊緣智能設備的實用深度學習(影印版) 內容簡介
無論你是一名渴望進入人工智能世界的軟件工程師,一名經驗豐富的數據科學家,還是一名懷揣創造下一個人工智能爆款應用偉大夢想的業余愛好者,你可能都想知道從哪里開始深度學習。這本循序漸進的指導書會教你如何通過實際動手操作的方式為云計算、移動端、瀏覽器和邊緣設備構建實用的深度學習應用程序。
云、移動端和邊緣智能設備的實用深度學習(影印版) 目錄
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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