Description
Practical Machine Learning in JavaScript, 1st ed.
TensorFlow.js for Web Developers
Author: Gerard Charlie
Language: EnglishKeywords
TensorFlow; TensorFlow.js; Machine Learning; Deep Learning; JavaScript; ML; DL; AI; Artificial Intelligence; Neural Networks
323 p. · 15.5x23.5 cm · Paperback
Description
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Build machine learning web applications without having to learn a new language. This book will help you develop basic knowledge of machine learning concepts and applications.
You?ll learn not only theory, but also dive into code samples and example projects with TensorFlow.js. Using these skills and your knowledge as a web developer, you?ll add a whole new field of development to your tool set. This will give you a more concrete understanding of the possibilities offered by machine learning. Discover how ML will impact the future of not just programming in general, but web development specifically.
Machine learning is currently one of the most exciting technology fields with the potential to impact industries from health to home automation to retail, and even art. Google has now introduced TensorFlow.js?an iteration of TensorFlow aimed directly at web developers. Practical Machine Learning in JavaScript will help you stay relevant in the tech industry with new tools, trends, and best practices.
- Use the JavaScript framework for ML
- Build machine learning applications for the web
- Develop dynamic and intelligent web content
Web developers and who want a hands-on introduction to machine learning in JavaScript. A working knowledge of the JavaScript language is recommended.
Chapter 1: Introduction to Machine Learning
• Definition
• Explanation of concepts• Algorithms
• Examples of impact
Chapter 2: Basics of Tensorflow.js
• What is Tensorflow.js?
• Features
Chapter 3: Building an Image Classifier
• Using a pre-trained model
• Creating a custom model
• Saving and loading a model
Chapter 4: Building a Sentiment Analysis System
• Train a model with text data• Create text-based ML applications
Chapter 5: Experimenting with Inputs
• Using ML with electronics data
• Using audio data
Chapter 6: Deploying Models
Chapter7: Ethics in AIMove from basic web development into the field of machine learning
Incorporate the ethics of AI into your development considerations
Harness your existing skills with JavaScript to learn a new approach to development
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