MobileNet and EfficientNet for Edge Deployment
Lightweight architectures, TFLite conversion, model size vs accuracy tradeoffs.
Why Edge Models Differ
On phones and embedded devices you trade some accuracy for tiny size, low latency, and low power. MobileNet and EfficientNet are designed for exactly this, using efficient building blocks instead of heavy dense convolutions.
MobileNet Depthwise Convolutions
MobileNet replaces standard convolutions with depthwise separable convolutions: a per-channel spatial filter followed by a 1x1 pointwise mix. This cuts compute and parameters by roughly 8-9x with little accuracy loss.
All lessons in this course
- Transfer Learning Concepts and Strategies
- Using VGG16 and ResNet50 as Base Models
- Fine-tuning: Unfreezing and Retraining
- MobileNet and EfficientNet for Edge Deployment