- 云移动端和边缘智能设备的实用深度学习(影印版)(英文版)
- - 作者：(美)安尼如德·科尔//悉达哈·甘菊//梅赫尔·卡萨姆|责编:张烨
  - 出版社：东南大学
  - ISBN：9787564188825
  - 出版日期：2020/06/01
  - 页数：588
- 售价：55.2

内容大纲
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，你都想知道要从哪里开始。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、移动端、浏览器和边缘设备构建实用的深度学习应用程序。
Anirudh Koul、Siddha Ganju和Meher Kasam三位作者凭借多年的行业经验将深度学习研究转化为获奖的应用程序，指导你将想法转化为现实世界中的人们可以使用的产品。
作者介绍
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

内容大纲

作者介绍

目录

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