AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence

AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence
PDF, ePUB

Book Description
If you’re looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.
You’ll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code.
You’ll learn:
  • How to build models with TensorFlow using skills that employers desire
  • The basics of machine learning by working with code samples
  • How to implement computer vision, including feature detection in images
  • How to use NLP to tokenize and sequence words and sentences
  • Methods for embedding models in Android and iOS
  • How to serve models over the web and in the cloud with TensorFlow Serving

Content

I. Building Models
1. Introduction to TensorFlow
2. Introduction to Computer Vision
3. Going Beyond the Basics: Detecting Features in Images
4. Using Public Datasets with TensorFlow Datasets
5. Introduction to Natural Language Processing
6. Making Sentiment Programmable Using Embeddings
7. Recurrent Neural Networks for Natural Language Processing
8. Using TensorFlow to Create Text
9. Understanding Sequence and Time Series Data
10. Creating ML Models to Predict Sequences
11. Using Convolutional and Recurrent Methods for Sequence Models

II. Using Models
12. An Introduction to TensorFlow Lite
13. Using TensorFlow Lite in Android Apps
14. Using TensorFlow Lite in iOS Apps
15. An Introduction to TensorFlow.js
16. Coding Techniques for Computer Vision in TensorFlow.js
17. Reusing and Converting Python Models to jаvascript
18. Transfer Learning in jаvascript
19. Deployment with TensorFlow Serving
20. AI Ethics, Fairness, and Privacy

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