Advanced UX with TensorFlow.js

Overview

Explore advanced user experience techniques using TensorFlow.js, enhancing web applications with machine learning capabilities for improved interactivity and functionality.

Syllabus

• Introduction to TensorFlow.js for UX
Overview of TensorFlow.js
Benefits of integrating machine learning into UX
Setting up the development environment
• Core Concepts of TensorFlow.js
Understanding Tensors and Operations
Models in TensorFlow.js: Pre-trained and Custom
Data Handling and Preprocessing
• Enhancing User Experience with TensorFlow.js
Using ML Models for User Interaction
Real-time Predictions in Web Applications
• Designing Intuitive ML-Driven Interfaces
Best Practices for ML UX Design
Case Studies: Successful ML Integrations in UX
• Building Interactive Applications
Hands-on Project: Developing a Custom Image Classifier
Implementing Sound Recognition Models for UX
• Performance Optimization
Understanding Model Efficiency and Speed
Reducing Load Times and Model Size
• Deployment and Integration
Deploying TensorFlow.js Models in Production
Integrating with Frontend Frameworks (e.g., React, Vue)
• Testing and Evaluation
Techniques for Testing User Experience with ML Features
Gathering and Analyzing User Feedback
• Ethical Considerations and Accessibility in ML UX
Designing Inclusive and Accessible ML Features
Addressing Bias and Ethics in User-Centric AI Applications
• Future Trends and Emerging Technologies
Exploring Future Use Cases of AI in UX
Staying Updated with TensorFlow.js and UX Innovations
• Final Project
Conceptualizing and Building an Advanced UX Application
Peer Reviews and Iterative Improvements

Subjects

Conference Talks