TensorFlow deployment: browser-based TF.js, device-based TF Lite, data pipelines, and optimization.
TensorFlow: Data and Deployment Specialization
4 Courses
- Browser-based Models with TensorFlow.js
- Device-based Models with TensorFlow Lite
- Data Pipelines with TensorFlow Data Services
- Advanced Deployment Scenarios with TensorFlow
TF Lite Benefits
- Lightweight + low-latency + privacy
- Improved power consumption
- Efficient model ready to use
Optimization Techniques
- Quantization (all CPU platforms, reduced latency, low memory)
- Weight pruning
- Model topology transforms
- Tensor decomposition
- Distillation
TensorFlow #EdgeAI #MobileML #FarshidPirahansiah
Source: Pirahansiah, F. “TensorFlow Deployment Specialization”. pirahansiah.com, updated 2026-09-19. Canonical URL https://pirahansiah.com/farshid/content/course-tensorflow-deploy/ · markdown source course-tensorflow-deploy.md · how to cite, quote and link this site.