AI with JavaScript: Building Machine Learning Applications in the Browser

Overview

Explore browser-based AI development using TensorFlow.js and Transformers.js, covering practical implementations, benefits, and challenges of running machine learning models directly in web browsers.

Syllabus

• **Introduction to AI and JavaScript**
Overview of AI and its applications
Introduction to JavaScript and its role in AI development
Setting up the development environment
• **Introduction to TensorFlow.js**
Overview of TensorFlow.js
Installing and setting up TensorFlow.js
Basic operations and tensors
• **Building Neural Networks in the Browser**
Understanding neural networks
Creating simple neural networks with TensorFlow.js
Training and evaluating models directly in the browser
• **Data Handling and Preprocessing in JavaScript**
Loading and manipulating datasets
Data preprocessing techniques
Working with JSON and CSV formats
• **Image Classification in TensorFlow.js**
Introduction to image classification
Building a simple image classification model
Pre-built models and transfer learning with TensorFlow.js
• **Natural Language Processing with Transformers.js**
Overview of Transformers.js
Implementing NLP tasks in the browser
Sentiment analysis and text generation
• **Model Optimization and Performance**
Techniques for optimizing model performance
Reducing model size with quantization
Managing browser resources efficiently
• **Benefits and Challenges of Browser-Based AI**
Advantages of running AI models in the browser
Limitations and challenges
Privacy considerations and data security
• **Case Studies and Real-World Applications**
Examples of browser-based AI applications
Discussion of practical implementations
Future trends in AI development with JavaScript
• **Final Project**
Implementing a full browser-based AI application
Presentation and sharing of projects
Feedback and course closure

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Subjects

Programming